---
_id: '15009'
author:
- first_name: Nico
full_name: Epple, Nico
last_name: Epple
- first_name: Simone
full_name: Dari, Simone
last_name: Dari
- first_name: Ludwig
full_name: Drees, Ludwig
last_name: Drees
- first_name: Valentin
full_name: Protschky, Valentin
last_name: Protschky
- first_name: Andreas
full_name: Riener, Andreas
last_name: Riener
citation:
ama: 'Epple N, Dari S, Drees L, Protschky V, Riener A. Influence of Cruise Control
on Driver Guidance - a Comparison between System Generations and Countries. In:
2019 IEEE Intelligent Vehicles Symposium (IV). ; 2019. doi:10.1109/ivs.2019.8814100'
apa: Epple, N., Dari, S., Drees, L., Protschky, V., & Riener, A. (2019). Influence
of Cruise Control on Driver Guidance - a Comparison between System Generations
and Countries. In 2019 IEEE Intelligent Vehicles Symposium (IV). https://doi.org/10.1109/ivs.2019.8814100
bibtex: '@inproceedings{Epple_Dari_Drees_Protschky_Riener_2019, title={Influence
of Cruise Control on Driver Guidance - a Comparison between System Generations
and Countries}, DOI={10.1109/ivs.2019.8814100},
booktitle={2019 IEEE Intelligent Vehicles Symposium (IV)}, author={Epple, Nico
and Dari, Simone and Drees, Ludwig and Protschky, Valentin and Riener, Andreas},
year={2019} }'
chicago: Epple, Nico, Simone Dari, Ludwig Drees, Valentin Protschky, and Andreas
Riener. “Influence of Cruise Control on Driver Guidance - a Comparison between
System Generations and Countries.” In 2019 IEEE Intelligent Vehicles Symposium
(IV), 2019. https://doi.org/10.1109/ivs.2019.8814100.
ieee: N. Epple, S. Dari, L. Drees, V. Protschky, and A. Riener, “Influence of Cruise
Control on Driver Guidance - a Comparison between System Generations and Countries,”
in 2019 IEEE Intelligent Vehicles Symposium (IV), 2019.
mla: Epple, Nico, et al. “Influence of Cruise Control on Driver Guidance - a Comparison
between System Generations and Countries.” 2019 IEEE Intelligent Vehicles Symposium
(IV), 2019, doi:10.1109/ivs.2019.8814100.
short: 'N. Epple, S. Dari, L. Drees, V. Protschky, A. Riener, in: 2019 IEEE Intelligent
Vehicles Symposium (IV), 2019.'
date_created: 2019-11-15T10:54:04Z
date_updated: 2022-01-06T06:52:14Z
department:
- _id: '34'
- _id: '355'
doi: 10.1109/ivs.2019.8814100
language:
- iso: eng
publication: 2019 IEEE Intelligent Vehicles Symposium (IV)
publication_identifier:
isbn:
- '9781728105604'
publication_status: published
status: public
title: Influence of Cruise Control on Driver Guidance - a Comparison between System
Generations and Countries
type: conference
user_id: '315'
year: '2019'
...
---
_id: '15011'
author:
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Recommendation:
From Collaborative Filtering to Dyad Ranking. In: Hoffmann F, Hüllermeier E, Mikut
R, eds. Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28.
- 29. November 2019. KIT Scientific Publishing, Karlsruhe; 2019:135-146.'
apa: 'Tornede, A., Wever, M. D., & Hüllermeier, E. (2019). Algorithm Selection
as Recommendation: From Collaborative Filtering to Dyad Ranking. In F. Hoffmann,
E. Hüllermeier, & R. Mikut (Eds.), Proceedings - 29. Workshop Computational
Intelligence, Dortmund, 28. - 29. November 2019 (pp. 135–146). Dortmund: KIT
Scientific Publishing, Karlsruhe.'
bibtex: '@inproceedings{Tornede_Wever_Hüllermeier_2019, title={Algorithm Selection
as Recommendation: From Collaborative Filtering to Dyad Ranking}, booktitle={Proceedings
- 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019},
publisher={KIT Scientific Publishing, Karlsruhe}, author={Tornede, Alexander and
Wever, Marcel Dominik and Hüllermeier, Eyke}, editor={Hoffmann, Frank and Hüllermeier,
Eyke and Mikut, RalfEditors}, year={2019}, pages={135–146} }'
chicago: 'Tornede, Alexander, Marcel Dominik Wever, and Eyke Hüllermeier. “Algorithm
Selection as Recommendation: From Collaborative Filtering to Dyad Ranking.” In
Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29.
November 2019, edited by Frank Hoffmann, Eyke Hüllermeier, and Ralf Mikut,
135–46. KIT Scientific Publishing, Karlsruhe, 2019.'
ieee: 'A. Tornede, M. D. Wever, and E. Hüllermeier, “Algorithm Selection as Recommendation:
From Collaborative Filtering to Dyad Ranking,” in Proceedings - 29. Workshop
Computational Intelligence, Dortmund, 28. - 29. November 2019, Dortmund, 2019,
pp. 135–146.'
mla: 'Tornede, Alexander, et al. “Algorithm Selection as Recommendation: From Collaborative
Filtering to Dyad Ranking.” Proceedings - 29. Workshop Computational Intelligence,
Dortmund, 28. - 29. November 2019, edited by Frank Hoffmann et al., KIT Scientific
Publishing, Karlsruhe, 2019, pp. 135–46.'
short: 'A. Tornede, M.D. Wever, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier,
R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, Dortmund,
28. - 29. November 2019, KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–146.'
conference:
end_date: 2019-11-29
location: Dortmund
name: 29. Workshop Computational Intelligence
start_date: 2019-11-28
date_created: 2019-11-15T13:29:25Z
date_updated: 2022-01-06T06:52:14Z
ddc:
- '006'
department:
- _id: '355'
editor:
- first_name: Frank
full_name: Hoffmann, Frank
last_name: Hoffmann
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: Ralf
full_name: Mikut, Ralf
last_name: Mikut
file:
- access_level: open_access
content_type: application/pdf
creator: ahetzer
date_created: 2020-05-25T08:01:31Z
date_updated: 2020-05-25T08:01:31Z
file_id: '17060'
file_name: ci_workshop_tornede.pdf
file_size: 468825
relation: main_file
file_date_updated: 2020-05-25T08:01:31Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 135-146
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28.
- 29. November 2019
publication_identifier:
isbn:
- 978-3-7315-0979-0
publication_status: published
publisher: KIT Scientific Publishing, Karlsruhe
status: public
title: 'Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad
Ranking'
type: conference
user_id: '38209'
year: '2019'
...
---
_id: '15013'
author:
- first_name: Klaus
full_name: Brinker, Klaus
last_name: Brinker
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Brinker K, Hüllermeier E. A Reduction of Label Ranking to Multiclass Classification.
In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge
Discovery in Databases. Würzburg, Germany; 2019.'
apa: Brinker, K., & Hüllermeier, E. (2019). A Reduction of Label Ranking to
Multiclass Classification. In Proceedings ECML/PKDD, European Conference on
Machine Learning and Knowledge Discovery in Databases. Würzburg, Germany.
bibtex: '@inproceedings{Brinker_Hüllermeier_2019, place={Würzburg, Germany}, title={A
Reduction of Label Ranking to Multiclass Classification}, booktitle={Proceedings
ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in
Databases}, author={Brinker, Klaus and Hüllermeier, Eyke}, year={2019} }'
chicago: Brinker, Klaus, and Eyke Hüllermeier. “A Reduction of Label Ranking to
Multiclass Classification.” In Proceedings ECML/PKDD, European Conference on
Machine Learning and Knowledge Discovery in Databases. Würzburg, Germany,
2019.
ieee: K. Brinker and E. Hüllermeier, “A Reduction of Label Ranking to Multiclass
Classification,” in Proceedings ECML/PKDD, European Conference on Machine Learning
and Knowledge Discovery in Databases, 2019.
mla: Brinker, Klaus, and Eyke Hüllermeier. “A Reduction of Label Ranking to Multiclass
Classification.” Proceedings ECML/PKDD, European Conference on Machine Learning
and Knowledge Discovery in Databases, 2019.
short: 'K. Brinker, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference
on Machine Learning and Knowledge Discovery in Databases, Würzburg, Germany, 2019.'
date_created: 2019-11-18T07:26:43Z
date_updated: 2022-01-06T06:52:14Z
department:
- _id: '34'
- _id: '355'
- _id: '7'
language:
- iso: eng
place: Würzburg, Germany
publication: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge
Discovery in Databases
status: public
title: A Reduction of Label Ranking to Multiclass Classification
type: conference
user_id: '315'
year: '2019'
...
---
_id: '15014'
author:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Ines
full_name: Couso, Ines
last_name: Couso
- first_name: Sebastian
full_name: Diestercke, Sebastian
last_name: Diestercke
citation:
ama: 'Hüllermeier E, Couso I, Diestercke S. Learning from Imprecise Data: Adjustments
of Optimistic and Pessimistic Variants. In: Proceedings SUM 2019, International
Conference on Scalable Uncertainty Management. ; 2019.'
apa: 'Hüllermeier, E., Couso, I., & Diestercke, S. (2019). Learning from Imprecise
Data: Adjustments of Optimistic and Pessimistic Variants. In Proceedings SUM
2019, International Conference on Scalable Uncertainty Management.'
bibtex: '@inproceedings{Hüllermeier_Couso_Diestercke_2019, title={Learning from
Imprecise Data: Adjustments of Optimistic and Pessimistic Variants}, booktitle={Proceedings
SUM 2019, International Conference on Scalable Uncertainty Management}, author={Hüllermeier,
Eyke and Couso, Ines and Diestercke, Sebastian}, year={2019} }'
chicago: 'Hüllermeier, Eyke, Ines Couso, and Sebastian Diestercke. “Learning from
Imprecise Data: Adjustments of Optimistic and Pessimistic Variants.” In Proceedings
SUM 2019, International Conference on Scalable Uncertainty Management, 2019.'
ieee: 'E. Hüllermeier, I. Couso, and S. Diestercke, “Learning from Imprecise Data:
Adjustments of Optimistic and Pessimistic Variants,” in Proceedings SUM 2019,
International Conference on Scalable Uncertainty Management, 2019.'
mla: 'Hüllermeier, Eyke, et al. “Learning from Imprecise Data: Adjustments of Optimistic
and Pessimistic Variants.” Proceedings SUM 2019, International Conference on
Scalable Uncertainty Management, 2019.'
short: 'E. Hüllermeier, I. Couso, S. Diestercke, in: Proceedings SUM 2019, International
Conference on Scalable Uncertainty Management, 2019.'
date_created: 2019-11-18T07:38:13Z
date_updated: 2022-01-06T06:52:14Z
department:
- _id: '34'
- _id: '355'
- _id: '7'
language:
- iso: eng
publication: Proceedings SUM 2019, International Conference on Scalable Uncertainty
Management
status: public
title: 'Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants'
type: conference
user_id: '315'
year: '2019'
...
---
_id: '15015'
author:
- first_name: Sascha
full_name: Henzgen, Sascha
last_name: Henzgen
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Henzgen S, Hüllermeier E. Mining Rank Data. ACM Transactions on Knowledge
Discovery from Data. 2019:1-36. doi:10.1145/3363572
apa: Henzgen, S., & Hüllermeier, E. (2019). Mining Rank Data. ACM Transactions
on Knowledge Discovery from Data, 1–36. https://doi.org/10.1145/3363572
bibtex: '@article{Henzgen_Hüllermeier_2019, title={Mining Rank Data}, DOI={10.1145/3363572},
journal={ACM Transactions on Knowledge Discovery from Data}, author={Henzgen,
Sascha and Hüllermeier, Eyke}, year={2019}, pages={1–36} }'
chicago: Henzgen, Sascha, and Eyke Hüllermeier. “Mining Rank Data.” ACM Transactions
on Knowledge Discovery from Data, 2019, 1–36. https://doi.org/10.1145/3363572.
ieee: S. Henzgen and E. Hüllermeier, “Mining Rank Data,” ACM Transactions on
Knowledge Discovery from Data, pp. 1–36, 2019.
mla: Henzgen, Sascha, and Eyke Hüllermeier. “Mining Rank Data.” ACM Transactions
on Knowledge Discovery from Data, 2019, pp. 1–36, doi:10.1145/3363572.
short: S. Henzgen, E. Hüllermeier, ACM Transactions on Knowledge Discovery from
Data (2019) 1–36.
date_created: 2019-11-18T07:40:27Z
date_updated: 2022-01-06T06:52:14Z
department:
- _id: '34'
- _id: '355'
- _id: '7'
doi: 10.1145/3363572
language:
- iso: eng
page: 1-36
publication: ACM Transactions on Knowledge Discovery from Data
publication_identifier:
issn:
- 1556-4681
publication_status: published
status: public
title: Mining Rank Data
type: journal_article
user_id: '315'
year: '2019'
...
---
_id: '14027'
author:
- first_name: Viktor
full_name: Bengs, Viktor
id: '76599'
last_name: Bengs
- first_name: Matthias
full_name: Eulert, Matthias
last_name: Eulert
- first_name: Hajo
full_name: Holzmann, Hajo
last_name: Holzmann
citation:
ama: Bengs V, Eulert M, Holzmann H. Asymptotic confidence sets for the jump curve
in bivariate regression problems. Journal of Multivariate Analysis. 2019:291-312.
doi:10.1016/j.jmva.2019.02.017
apa: Bengs, V., Eulert, M., & Holzmann, H. (2019). Asymptotic confidence sets
for the jump curve in bivariate regression problems. Journal of Multivariate
Analysis, 291–312. https://doi.org/10.1016/j.jmva.2019.02.017
bibtex: '@article{Bengs_Eulert_Holzmann_2019, title={Asymptotic confidence sets
for the jump curve in bivariate regression problems}, DOI={10.1016/j.jmva.2019.02.017},
journal={Journal of Multivariate Analysis}, author={Bengs, Viktor and Eulert,
Matthias and Holzmann, Hajo}, year={2019}, pages={291–312} }'
chicago: Bengs, Viktor, Matthias Eulert, and Hajo Holzmann. “Asymptotic Confidence
Sets for the Jump Curve in Bivariate Regression Problems.” Journal of Multivariate
Analysis, 2019, 291–312. https://doi.org/10.1016/j.jmva.2019.02.017.
ieee: V. Bengs, M. Eulert, and H. Holzmann, “Asymptotic confidence sets for the
jump curve in bivariate regression problems,” Journal of Multivariate Analysis,
pp. 291–312, 2019.
mla: Bengs, Viktor, et al. “Asymptotic Confidence Sets for the Jump Curve in Bivariate
Regression Problems.” Journal of Multivariate Analysis, 2019, pp. 291–312,
doi:10.1016/j.jmva.2019.02.017.
short: V. Bengs, M. Eulert, H. Holzmann, Journal of Multivariate Analysis (2019)
291–312.
date_created: 2019-10-30T14:22:57Z
date_updated: 2022-01-06T06:51:52Z
department:
- _id: '34'
- _id: '355'
doi: 10.1016/j.jmva.2019.02.017
language:
- iso: eng
page: 291-312
publication: Journal of Multivariate Analysis
publication_identifier:
issn:
- 0047-259X
publication_status: published
status: public
title: Asymptotic confidence sets for the jump curve in bivariate regression problems
type: journal_article
user_id: '76599'
year: '2019'
...
---
_id: '14028'
author:
- first_name: Viktor
full_name: Bengs, Viktor
id: '76599'
last_name: Bengs
- first_name: Hajo
full_name: Holzmann, Hajo
last_name: Holzmann
citation:
ama: Bengs V, Holzmann H. Adaptive confidence sets for kink estimation. Electronic
Journal of Statistics. 2019:1523-1579. doi:10.1214/19-ejs1555
apa: Bengs, V., & Holzmann, H. (2019). Adaptive confidence sets for kink estimation.
Electronic Journal of Statistics, 1523–1579. https://doi.org/10.1214/19-ejs1555
bibtex: '@article{Bengs_Holzmann_2019, title={Adaptive confidence sets for kink
estimation}, DOI={10.1214/19-ejs1555},
journal={Electronic Journal of Statistics}, author={Bengs, Viktor and Holzmann,
Hajo}, year={2019}, pages={1523–1579} }'
chicago: Bengs, Viktor, and Hajo Holzmann. “Adaptive Confidence Sets for Kink Estimation.”
Electronic Journal of Statistics, 2019, 1523–79. https://doi.org/10.1214/19-ejs1555.
ieee: V. Bengs and H. Holzmann, “Adaptive confidence sets for kink estimation,”
Electronic Journal of Statistics, pp. 1523–1579, 2019.
mla: Bengs, Viktor, and Hajo Holzmann. “Adaptive Confidence Sets for Kink Estimation.”
Electronic Journal of Statistics, 2019, pp. 1523–79, doi:10.1214/19-ejs1555.
short: V. Bengs, H. Holzmann, Electronic Journal of Statistics (2019) 1523–1579.
date_created: 2019-10-30T14:25:16Z
date_updated: 2022-01-06T06:51:52Z
department:
- _id: '34'
- _id: '355'
doi: 10.1214/19-ejs1555
language:
- iso: eng
page: 1523-1579
publication: Electronic Journal of Statistics
publication_identifier:
issn:
- 1935-7524
publication_status: published
status: public
title: Adaptive confidence sets for kink estimation
type: journal_article
user_id: '76599'
year: '2019'
...
---
_id: '13132'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Mohr F, Wever MD, Tornede A, Hüllermeier E. From Automated to On-The-Fly Machine
Learning. In: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik
Für Gesellschaft. INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft
für Informatik. Bonn: Gesellschaft für Informatik e.V.; 2019:273-274.'
apa: 'Mohr, F., Wever, M. D., Tornede, A., & Hüllermeier, E. (2019). From Automated
to On-The-Fly Machine Learning. In INFORMATIK 2019: 50 Jahre Gesellschaft für
Informatik – Informatik für Gesellschaft (pp. 273–274). Bonn: Gesellschaft
für Informatik e.V.'
bibtex: '@inproceedings{Mohr_Wever_Tornede_Hüllermeier_2019, place={Bonn}, series={INFORMATIK
2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik}, title={From
Automated to On-The-Fly Machine Learning}, booktitle={INFORMATIK 2019: 50 Jahre
Gesellschaft für Informatik – Informatik für Gesellschaft}, publisher={Gesellschaft
für Informatik e.V.}, author={Mohr, Felix and Wever, Marcel Dominik and Tornede,
Alexander and Hüllermeier, Eyke}, year={2019}, pages={273–274}, collection={INFORMATIK
2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik} }'
chicago: 'Mohr, Felix, Marcel Dominik Wever, Alexander Tornede, and Eyke Hüllermeier.
“From Automated to On-The-Fly Machine Learning.” In INFORMATIK 2019: 50 Jahre
Gesellschaft Für Informatik – Informatik Für Gesellschaft, 273–74. INFORMATIK
2019, Lecture Notes in Informatics (LNI), Gesellschaft Für Informatik. Bonn: Gesellschaft
für Informatik e.V., 2019.'
ieee: 'F. Mohr, M. D. Wever, A. Tornede, and E. Hüllermeier, “From Automated to
On-The-Fly Machine Learning,” in INFORMATIK 2019: 50 Jahre Gesellschaft für
Informatik – Informatik für Gesellschaft, Kassel, 2019, pp. 273–274.'
mla: 'Mohr, Felix, et al. “From Automated to On-The-Fly Machine Learning.” INFORMATIK
2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft,
Gesellschaft für Informatik e.V., 2019, pp. 273–74.'
short: 'F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, in: INFORMATIK 2019: 50
Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, Gesellschaft
für Informatik e.V., Bonn, 2019, pp. 273–274.'
conference:
end_date: 2019-09-26
location: Kassel
name: Informatik 2019
start_date: 2019-09-23
date_created: 2019-09-04T08:44:46Z
date_updated: 2022-01-06T06:51:28Z
department:
- _id: '355'
language:
- iso: eng
page: ' 273-274 '
place: Bonn
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: 'INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für
Gesellschaft'
publisher: Gesellschaft für Informatik e.V.
series_title: INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft für
Informatik
status: public
title: From Automated to On-The-Fly Machine Learning
type: conference_abstract
user_id: '38209'
year: '2019'
...
---
_id: '10232'
abstract:
- lang: eng
text: Existing tools for automated machine learning, such as Auto-WEKA, TPOT, auto-sklearn,
and more recently ML-Plan, have shown impressive results for the tasks of single-label
classification and regression. Yet, there is only little work on other types of
machine learning problems so far. In particular, there is almost no work on automating
the engineering of machine learning solutions for multi-label classification (MLC).
We show how the scope of ML-Plan, an AutoML-tool for multi-class classification,
can be extended towards MLC using MEKA, which is a multi-label extension of the
well-known Java library WEKA. The resulting approach recursively refines MEKA's
multi-label classifiers, nesting other multi-label classifiers for meta algorithms
and single-label classifiers provided by WEKA as base learners. In our evaluation,
we find that the proposed approach yields strong results and performs significantly
better than a set of baselines we compare with.
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Alexander
full_name: Tornede, Alexander
id: '38209'
last_name: Tornede
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Mohr F, Tornede A, Hüllermeier E. Automating Multi-Label Classification
Extending ML-Plan. In: ; 2019.'
apa: Wever, M. D., Mohr, F., Tornede, A., & Hüllermeier, E. (2019). Automating
Multi-Label Classification Extending ML-Plan. Presented at the 6th ICML Workshop
on Automated Machine Learning (AutoML 2019), Long Beach, CA, USA.
bibtex: '@inproceedings{Wever_Mohr_Tornede_Hüllermeier_2019, title={Automating Multi-Label
Classification Extending ML-Plan}, author={Wever, Marcel Dominik and Mohr, Felix
and Tornede, Alexander and Hüllermeier, Eyke}, year={2019} }'
chicago: Wever, Marcel Dominik, Felix Mohr, Alexander Tornede, and Eyke Hüllermeier.
“Automating Multi-Label Classification Extending ML-Plan,” 2019.
ieee: M. D. Wever, F. Mohr, A. Tornede, and E. Hüllermeier, “Automating Multi-Label
Classification Extending ML-Plan,” presented at the 6th ICML Workshop on Automated
Machine Learning (AutoML 2019), Long Beach, CA, USA, 2019.
mla: Wever, Marcel Dominik, et al. Automating Multi-Label Classification Extending
ML-Plan. 2019.
short: 'M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.'
conference:
end_date: 2019-06-15
location: Long Beach, CA, USA
name: 6th ICML Workshop on Automated Machine Learning (AutoML 2019)
start_date: 2019-06-09
date_created: 2019-06-11T21:33:06Z
date_updated: 2022-01-06T06:50:33Z
ddc:
- '006'
department:
- _id: '355'
file:
- access_level: open_access
content_type: application/pdf
creator: wever
date_created: 2019-09-10T08:19:01Z
date_updated: 2019-09-10T08:20:44Z
file_id: '13177'
file_name: Automating_MultiLabel_Classification_Extending_ML-Plan.pdf
file_size: 388191
relation: main_file
file_date_updated: 2019-09-10T08:20:44Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
status: public
title: Automating Multi-Label Classification Extending ML-Plan
type: conference
user_id: '33176'
year: '2019'
...
---
_id: '20243'
author:
- first_name: Katharina
full_name: Rohlfing, Katharina
id: '50352'
last_name: Rohlfing
- first_name: Giuseppe
full_name: Leonardi, Giuseppe
last_name: Leonardi
- first_name: Iris
full_name: Nomikou, Iris
last_name: Nomikou
- first_name: Joanna
full_name: Rączaszek-Leonardi, Joanna
last_name: Rączaszek-Leonardi
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Rohlfing K, Leonardi G, Nomikou I, Rączaszek-Leonardi J, Hüllermeier E. Multimodal
Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches. IEEE
Transactions on Cognitive and Developmental Systems. Published online 2019.
doi:10.1109/TCDS.2019.2892991'
apa: 'Rohlfing, K., Leonardi, G., Nomikou, I., Rączaszek-Leonardi, J., & Hüllermeier,
E. (2019). Multimodal Turn-Taking: Motivations, Methodological Challenges, and
Novel Approaches. IEEE Transactions on Cognitive and Developmental Systems.
https://doi.org/10.1109/TCDS.2019.2892991'
bibtex: '@article{Rohlfing_Leonardi_Nomikou_Rączaszek-Leonardi_Hüllermeier_2019,
title={Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel
Approaches}, DOI={10.1109/TCDS.2019.2892991},
journal={IEEE Transactions on Cognitive and Developmental Systems}, author={Rohlfing,
Katharina and Leonardi, Giuseppe and Nomikou, Iris and Rączaszek-Leonardi, Joanna
and Hüllermeier, Eyke}, year={2019} }'
chicago: 'Rohlfing, Katharina, Giuseppe Leonardi, Iris Nomikou, Joanna Rączaszek-Leonardi,
and Eyke Hüllermeier. “Multimodal Turn-Taking: Motivations, Methodological Challenges,
and Novel Approaches.” IEEE Transactions on Cognitive and Developmental Systems,
2019. https://doi.org/10.1109/TCDS.2019.2892991.'
ieee: 'K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, and E. Hüllermeier,
“Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches,”
IEEE Transactions on Cognitive and Developmental Systems, 2019, doi: 10.1109/TCDS.2019.2892991.'
mla: 'Rohlfing, Katharina, et al. “Multimodal Turn-Taking: Motivations, Methodological
Challenges, and Novel Approaches.” IEEE Transactions on Cognitive and Developmental
Systems, 2019, doi:10.1109/TCDS.2019.2892991.'
short: K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, E. Hüllermeier,
IEEE Transactions on Cognitive and Developmental Systems (2019).
date_created: 2020-11-02T13:25:49Z
date_updated: 2023-02-01T12:39:19Z
department:
- _id: '749'
- _id: '355'
doi: 10.1109/TCDS.2019.2892991
language:
- iso: eng
publication: IEEE Transactions on Cognitive and Developmental Systems
status: public
title: 'Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel
Approaches'
type: journal_article
user_id: '14931'
year: '2019'
...
---
_id: '2479'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Amin
full_name: Faez, Amin
last_name: Faez
citation:
ama: 'Mohr F, Wever MD, Hüllermeier E, Faez A. (WIP) Towards the Automated Composition
of Machine Learning Services. In: SCC. San Francisco, CA, USA: IEEE; 2018.
doi:10.1109/SCC.2018.00039'
apa: 'Mohr, F., Wever, M. D., Hüllermeier, E., & Faez, A. (2018). (WIP) Towards
the Automated Composition of Machine Learning Services. In SCC. San Francisco,
CA, USA: IEEE. https://doi.org/10.1109/SCC.2018.00039'
bibtex: '@inproceedings{Mohr_Wever_Hüllermeier_Faez_2018, place={San Francisco,
CA, USA}, title={(WIP) Towards the Automated Composition of Machine Learning Services},
DOI={10.1109/SCC.2018.00039},
booktitle={SCC}, publisher={IEEE}, author={Mohr, Felix and Wever, Marcel Dominik
and Hüllermeier, Eyke and Faez, Amin}, year={2018} }'
chicago: 'Mohr, Felix, Marcel Dominik Wever, Eyke Hüllermeier, and Amin Faez. “(WIP)
Towards the Automated Composition of Machine Learning Services.” In SCC.
San Francisco, CA, USA: IEEE, 2018. https://doi.org/10.1109/SCC.2018.00039.'
ieee: F. Mohr, M. D. Wever, E. Hüllermeier, and A. Faez, “(WIP) Towards the Automated
Composition of Machine Learning Services,” in SCC, San Francisco, CA, USA,
2018.
mla: Mohr, Felix, et al. “(WIP) Towards the Automated Composition of Machine Learning
Services.” SCC, IEEE, 2018, doi:10.1109/SCC.2018.00039.
short: 'F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: SCC, IEEE, San Francisco,
CA, USA, 2018.'
conference:
end_date: 2018-07-07
location: San Francisco, CA, USA
name: IEEE International Conference on Services Computing, SCC 2018
start_date: 2018-07-02
date_created: 2018-04-24T08:34:52Z
date_updated: 2022-01-06T06:56:35Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1109/SCC.2018.00039
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:08:39Z
date_updated: 2018-11-06T15:08:39Z
file_id: '5382'
file_name: 08456425.pdf
file_size: 237890
relation: main_file
file_date_updated: 2018-11-06T15:08:39Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://ieeexplore.ieee.org/document/8456425
oa: '1'
place: San Francisco, CA, USA
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: SCC
publication_status: published
publisher: IEEE
status: public
title: (WIP) Towards the Automated Composition of Machine Learning Services
type: conference
user_id: '49109'
year: '2018'
...
---
_id: '19524'
abstract:
- lang: eng
text: "Object ranking is an important problem in the realm of preference learning.\r\nOn
the basis of training data in the form of a set of rankings of objects,\r\nwhich
are typically represented as feature vectors, the goal is to learn a\r\nranking
function that predicts a linear order of any new set of objects.\r\nCurrent approaches
commonly focus on ranking by scoring, i.e., on learning an\r\nunderlying latent
utility function that seeks to capture the inherent utility\r\nof each object.
These approaches, however, are not able to take possible\r\neffects of context-dependence
into account, where context-dependence means that\r\nthe utility or usefulness
of an object may also depend on what other objects\r\nare available as alternatives.
In this paper, we formalize the problem of\r\ncontext-dependent ranking and present
two general approaches based on two\r\nnatural representations of context-dependent
ranking functions. Both approaches\r\nare instantiated by means of appropriate
neural network architectures, which\r\nare evaluated on suitable benchmark task."
author:
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
- first_name: Pritha
full_name: Gupta, Pritha
last_name: Gupta
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
citation:
ama: Pfannschmidt K, Gupta P, Hüllermeier E. Deep Architectures for Learning Context-dependent
Ranking Functions. arXiv:180305796. 2018.
apa: Pfannschmidt, K., Gupta, P., & Hüllermeier, E. (2018). Deep Architectures
for Learning Context-dependent Ranking Functions. ArXiv:1803.05796.
bibtex: '@article{Pfannschmidt_Gupta_Hüllermeier_2018, title={Deep Architectures
for Learning Context-dependent Ranking Functions}, journal={arXiv:1803.05796},
author={Pfannschmidt, Karlson and Gupta, Pritha and Hüllermeier, Eyke}, year={2018}
}'
chicago: Pfannschmidt, Karlson, Pritha Gupta, and Eyke Hüllermeier. “Deep Architectures
for Learning Context-Dependent Ranking Functions.” ArXiv:1803.05796, 2018.
ieee: K. Pfannschmidt, P. Gupta, and E. Hüllermeier, “Deep Architectures for Learning
Context-dependent Ranking Functions,” arXiv:1803.05796. 2018.
mla: Pfannschmidt, Karlson, et al. “Deep Architectures for Learning Context-Dependent
Ranking Functions.” ArXiv:1803.05796, 2018.
short: K. Pfannschmidt, P. Gupta, E. Hüllermeier, ArXiv:1803.05796 (2018).
date_created: 2020-09-17T10:53:39Z
date_updated: 2022-01-06T06:54:06Z
department:
- _id: '7'
- _id: '355'
language:
- iso: eng
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: arXiv:1803.05796
status: public
title: Deep Architectures for Learning Context-dependent Ranking Functions
type: preprint
user_id: '13472'
year: '2018'
...
---
_id: '2857'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Theodor
full_name: Lettmann, Theodor
id: '315'
last_name: Lettmann
orcid: 0000-0001-5859-2457
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
citation:
ama: 'Mohr F, Lettmann T, Hüllermeier E, Wever MD. Programmatic Task Network Planning.
In: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning. AAAI;
2018:31-39.'
apa: 'Mohr, F., Lettmann, T., Hüllermeier, E., & Wever, M. D. (2018). Programmatic
Task Network Planning. In Proceedings of the 1st ICAPS Workshop on Hierarchical
Planning (pp. 31–39). Delft, Netherlands: AAAI.'
bibtex: '@inproceedings{Mohr_Lettmann_Hüllermeier_Wever_2018, title={Programmatic
Task Network Planning}, booktitle={Proceedings of the 1st ICAPS Workshop on Hierarchical
Planning}, publisher={AAAI}, author={Mohr, Felix and Lettmann, Theodor and Hüllermeier,
Eyke and Wever, Marcel Dominik}, year={2018}, pages={31–39} }'
chicago: Mohr, Felix, Theodor Lettmann, Eyke Hüllermeier, and Marcel Dominik Wever.
“Programmatic Task Network Planning.” In Proceedings of the 1st ICAPS Workshop
on Hierarchical Planning, 31–39. AAAI, 2018.
ieee: F. Mohr, T. Lettmann, E. Hüllermeier, and M. D. Wever, “Programmatic Task
Network Planning,” in Proceedings of the 1st ICAPS Workshop on Hierarchical
Planning, Delft, Netherlands, 2018, pp. 31–39.
mla: Mohr, Felix, et al. “Programmatic Task Network Planning.” Proceedings of
the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.
short: 'F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the
1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.'
conference:
end_date: 2018-06-29
location: Delft, Netherlands
name: 28th International Conference on Automated Planning and Scheduling
start_date: 2018-06-24
date_created: 2018-05-24T09:00:20Z
date_updated: 2022-01-06T06:58:08Z
ddc:
- '000'
department:
- _id: '355'
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:18:26Z
date_updated: 2018-11-06T15:18:26Z
file_id: '5384'
file_name: Mohr18ProgrammaticPlanning.pdf
file_size: 349958
relation: main_file
success: 1
file_date_updated: 2018-11-06T15:18:26Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://icaps18.icaps-conference.org/fileadmin/alg/conferences/icaps18/workshops/workshop08/docs/Mohr18ProgrammaticPlanning.pdf
oa: '1'
page: 31-39
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning
publisher: AAAI
status: public
title: Programmatic Task Network Planning
type: conference
user_id: '315'
year: '2018'
...
---
_id: '24150'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Shalabh
full_name: Bhatnagar, Shalabh
last_name: Bhatnagar
citation:
ama: Ramaswamy A, Bhatnagar S. Stability of stochastic approximations with “controlled
markov” noise and temporal difference learning. IEEE Transactions on Automatic
Control. 2018;64(6):2614-2620.
apa: Ramaswamy, A., & Bhatnagar, S. (2018). Stability of stochastic approximations
with “controlled markov” noise and temporal difference learning. IEEE Transactions
on Automatic Control, 64(6), 2614–2620.
bibtex: '@article{Ramaswamy_Bhatnagar_2018, title={Stability of stochastic approximations
with “controlled markov” noise and temporal difference learning}, volume={64},
number={6}, journal={IEEE Transactions on Automatic Control}, publisher={IEEE},
author={Ramaswamy, Arunselvan and Bhatnagar, Shalabh}, year={2018}, pages={2614–2620}
}'
chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stability of Stochastic
Approximations with ‘Controlled Markov’ Noise and Temporal Difference Learning.”
IEEE Transactions on Automatic Control 64, no. 6 (2018): 2614–20.'
ieee: A. Ramaswamy and S. Bhatnagar, “Stability of stochastic approximations with
‘controlled markov’ noise and temporal difference learning,” IEEE Transactions
on Automatic Control, vol. 64, no. 6, pp. 2614–2620, 2018.
mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stability of Stochastic Approximations
with ‘Controlled Markov’ Noise and Temporal Difference Learning.” IEEE Transactions
on Automatic Control, vol. 64, no. 6, IEEE, 2018, pp. 2614–20.
short: A. Ramaswamy, S. Bhatnagar, IEEE Transactions on Automatic Control 64 (2018)
2614–2620.
date_created: 2021-09-10T10:17:54Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
intvolume: ' 64'
issue: '6'
language:
- iso: eng
page: 2614-2620
publication: IEEE Transactions on Automatic Control
publisher: IEEE
status: public
title: Stability of stochastic approximations with “controlled markov” noise and temporal
difference learning
type: journal_article
user_id: '66937'
volume: 64
year: '2018'
...
---
_id: '24151'
author:
- first_name: Burak
full_name: Demirel, Burak
last_name: Demirel
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Daniel E
full_name: Quevedo, Daniel E
last_name: Quevedo
- first_name: Holger
full_name: Karl, Holger
last_name: Karl
citation:
ama: 'Demirel B, Ramaswamy A, Quevedo DE, Karl H. Deepcas: A deep reinforcement
learning algorithm for control-aware scheduling. IEEE Control Systems Letters.
2018;2(4):737-742.'
apa: 'Demirel, B., Ramaswamy, A., Quevedo, D. E., & Karl, H. (2018). Deepcas:
A deep reinforcement learning algorithm for control-aware scheduling. IEEE
Control Systems Letters, 2(4), 737–742.'
bibtex: '@article{Demirel_Ramaswamy_Quevedo_Karl_2018, title={Deepcas: A deep reinforcement
learning algorithm for control-aware scheduling}, volume={2}, number={4}, journal={IEEE
Control Systems Letters}, publisher={IEEE}, author={Demirel, Burak and Ramaswamy,
Arunselvan and Quevedo, Daniel E and Karl, Holger}, year={2018}, pages={737–742}
}'
chicago: 'Demirel, Burak, Arunselvan Ramaswamy, Daniel E Quevedo, and Holger Karl.
“Deepcas: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling.”
IEEE Control Systems Letters 2, no. 4 (2018): 737–42.'
ieee: 'B. Demirel, A. Ramaswamy, D. E. Quevedo, and H. Karl, “Deepcas: A deep reinforcement
learning algorithm for control-aware scheduling,” IEEE Control Systems Letters,
vol. 2, no. 4, pp. 737–742, 2018.'
mla: 'Demirel, Burak, et al. “Deepcas: A Deep Reinforcement Learning Algorithm for
Control-Aware Scheduling.” IEEE Control Systems Letters, vol. 2, no. 4,
IEEE, 2018, pp. 737–42.'
short: B. Demirel, A. Ramaswamy, D.E. Quevedo, H. Karl, IEEE Control Systems Letters
2 (2018) 737–742.
date_created: 2021-09-10T10:19:07Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
intvolume: ' 2'
issue: '4'
language:
- iso: eng
page: 737-742
publication: IEEE Control Systems Letters
publisher: IEEE
status: public
title: 'Deepcas: A deep reinforcement learning algorithm for control-aware scheduling'
type: journal_article
user_id: '66937'
volume: 2
year: '2018'
...
---
_id: '2471'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Mohr F, Wever MD, Hüllermeier E. On-The-Fly Service Construction with Prototypes.
In: SCC. San Francisco, CA, USA: IEEE Computer Society; 2018. doi:10.1109/SCC.2018.00036'
apa: 'Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). On-The-Fly Service Construction
with Prototypes. In SCC. San Francisco, CA, USA: IEEE Computer Society.
https://doi.org/10.1109/SCC.2018.00036'
bibtex: '@inproceedings{Mohr_Wever_Hüllermeier_2018, place={San Francisco, CA, USA},
title={On-The-Fly Service Construction with Prototypes}, DOI={10.1109/SCC.2018.00036},
booktitle={SCC}, publisher={IEEE Computer Society}, author={Mohr, Felix and Wever,
Marcel Dominik and Hüllermeier, Eyke}, year={2018} }'
chicago: 'Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “On-The-Fly Service
Construction with Prototypes.” In SCC. San Francisco, CA, USA: IEEE Computer
Society, 2018. https://doi.org/10.1109/SCC.2018.00036.'
ieee: F. Mohr, M. D. Wever, and E. Hüllermeier, “On-The-Fly Service Construction
with Prototypes,” in SCC, San Francisco, CA, USA, 2018.
mla: Mohr, Felix, et al. “On-The-Fly Service Construction with Prototypes.” SCC,
IEEE Computer Society, 2018, doi:10.1109/SCC.2018.00036.
short: 'F. Mohr, M.D. Wever, E. Hüllermeier, in: SCC, IEEE Computer Society, San
Francisco, CA, USA, 2018.'
conference:
end_date: 2018-07-07
location: San Francisco, CA, USA
name: IEEE International Conference on Services Computing, SCC 2018
start_date: 2018-07-02
date_created: 2018-04-23T11:40:20Z
date_updated: 2022-01-06T06:56:32Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1109/SCC.2018.00036
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:15:38Z
date_updated: 2018-11-06T15:15:38Z
file_id: '5383'
file_name: 08456422.pdf
file_size: 356132
relation: main_file
success: 1
file_date_updated: 2018-11-06T15:15:38Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://ieeexplore.ieee.org/abstract/document/8456422
oa: '1'
place: San Francisco, CA, USA
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: SCC
publisher: IEEE Computer Society
status: public
title: On-The-Fly Service Construction with Prototypes
type: conference
user_id: '49109'
year: '2018'
...
---
_id: '3402'
abstract:
- lang: eng
text: In machine learning, so-called nested dichotomies are utilized as a reduction
technique, i.e., to decompose a multi-class classification problem into a set
of binary problems, which are solved using a simple binary classifier as a base
learner. The performance of the (multi-class) classifier thus produced strongly
depends on the structure of the decomposition. In this paper, we conduct an empirical
study, in which we compare existing heuristics for selecting a suitable structure
in the form of a nested dichotomy. Moreover, we propose two additional heuristics
as natural completions. One of them is the Best-of-K heuristic, which picks the
(presumably) best among K randomly generated nested dichotomies. Surprisingly,
and in spite of its simplicity, it turns out to outperform the state of the art.
author:
- first_name: Vitalik
full_name: Melnikov, Vitalik
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. On the effectiveness of heuristics for learning
nested dichotomies: an empirical analysis. Machine Learning. 2018. doi:10.1007/s10994-018-5733-1'
apa: 'Melnikov, V., & Hüllermeier, E. (2018). On the effectiveness of heuristics
for learning nested dichotomies: an empirical analysis. Machine Learning.
https://doi.org/10.1007/s10994-018-5733-1'
bibtex: '@article{Melnikov_Hüllermeier_2018, title={On the effectiveness of heuristics
for learning nested dichotomies: an empirical analysis}, DOI={10.1007/s10994-018-5733-1},
journal={Machine Learning}, author={Melnikov, Vitalik and Hüllermeier, Eyke},
year={2018} }'
chicago: 'Melnikov, Vitalik, and Eyke Hüllermeier. “On the Effectiveness of Heuristics
for Learning Nested Dichotomies: An Empirical Analysis.” Machine Learning,
2018. https://doi.org/10.1007/s10994-018-5733-1.'
ieee: 'V. Melnikov and E. Hüllermeier, “On the effectiveness of heuristics for learning
nested dichotomies: an empirical analysis,” Machine Learning, 2018.'
mla: 'Melnikov, Vitalik, and Eyke Hüllermeier. “On the Effectiveness of Heuristics
for Learning Nested Dichotomies: An Empirical Analysis.” Machine Learning,
2018, doi:10.1007/s10994-018-5733-1.'
short: V. Melnikov, E. Hüllermeier, Machine Learning (2018).
date_created: 2018-06-29T07:44:26Z
date_updated: 2022-01-06T06:59:14Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1007/s10994-018-5733-1
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T15:30:57Z
date_updated: 2018-11-02T15:30:57Z
file_id: '5305'
file_name: OnTheEffectivenessOfHeuristics.pdf
file_size: 1482882
relation: main_file
success: 1
file_date_updated: 2018-11-02T15:30:57Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '3'
name: SFB 901 - Project Area B
- _id: '1'
name: SFB 901
publication: Machine Learning
publication_identifier:
issn:
- 1573-0565
status: public
title: 'On the effectiveness of heuristics for learning nested dichotomies: an empirical
analysis'
type: journal_article
user_id: '15504'
year: '2018'
...
---
_id: '3510'
abstract:
- lang: eng
text: Automated machine learning (AutoML) seeks to automatically select, compose,
and parametrize machine learning algorithms, so as to achieve optimal performance
on a given task (dataset). Although current approaches to AutoML have already
produced impressive results, the field is still far from mature, and new techniques
are still being developed. In this paper, we present ML-Plan, a new approach to
AutoML based on hierarchical planning. To highlight the potential of this approach,
we compare ML-Plan to the state-of-the-art frameworks Auto-WEKA, auto-sklearn,
and TPOT. In an extensive series of experiments, we show that ML-Plan is highly
competitive and often outperforms existing approaches.
article_type: original
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Mohr F, Wever MD, Hüllermeier E. ML-Plan: Automated Machine Learning via Hierarchical
Planning. Machine Learning. Published online 2018:1495-1515. doi:10.1007/s10994-018-5735-z'
apa: 'Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). ML-Plan: Automated Machine
Learning via Hierarchical Planning. Machine Learning, 1495–1515. https://doi.org/10.1007/s10994-018-5735-z'
bibtex: '@article{Mohr_Wever_Hüllermeier_2018, title={ML-Plan: Automated Machine
Learning via Hierarchical Planning}, DOI={10.1007/s10994-018-5735-z},
journal={Machine Learning}, publisher={Springer}, author={Mohr, Felix and Wever,
Marcel Dominik and Hüllermeier, Eyke}, year={2018}, pages={1495–1515} }'
chicago: 'Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “ML-Plan: Automated
Machine Learning via Hierarchical Planning.” Machine Learning, 2018, 1495–1515.
https://doi.org/10.1007/s10994-018-5735-z.'
ieee: 'F. Mohr, M. D. Wever, and E. Hüllermeier, “ML-Plan: Automated Machine Learning
via Hierarchical Planning,” Machine Learning, pp. 1495–1515, 2018, doi:
10.1007/s10994-018-5735-z.'
mla: 'Mohr, Felix, et al. “ML-Plan: Automated Machine Learning via Hierarchical
Planning.” Machine Learning, Springer, 2018, pp. 1495–515, doi:10.1007/s10994-018-5735-z.'
short: F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018) 1495–1515.
conference:
end_date: 2018-09-14
location: Dublin, Ireland
name: European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases
start_date: 2018-09-10
date_created: 2018-07-08T14:06:14Z
date_updated: 2022-01-06T06:59:21Z
ddc:
- '000'
department:
- _id: '355'
- _id: '34'
- _id: '7'
- _id: '26'
doi: 10.1007/s10994-018-5735-z
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T15:32:16Z
date_updated: 2018-11-02T15:32:16Z
file_id: '5306'
file_name: ML-PlanAutomatedMachineLearnin.pdf
file_size: 1070937
relation: main_file
success: 1
file_date_updated: 2018-11-02T15:32:16Z
has_accepted_license: '1'
keyword:
- AutoML
- Hierarchical Planning
- HTN planning
- ML-Plan
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://rdcu.be/3Nc2
oa: '1'
page: 1495-1515
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Machine Learning
publication_identifier:
eissn:
- 1573-0565
issn:
- 0885-6125
publication_status: epub_ahead
publisher: Springer
status: public
title: 'ML-Plan: Automated Machine Learning via Hierarchical Planning'
type: journal_article
user_id: '5786'
year: '2018'
...
---
_id: '3552'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Mohr F, Wever MD, Hüllermeier E. Reduction Stumps for Multi-Class Classification.
In: Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch,
the Netherlands. doi:10.1007/978-3-030-01768-2_19'
apa: Mohr, F., Wever, M. D., & Hüllermeier, E. (n.d.). Reduction Stumps for
Multi-Class Classification. In Proceedings of the Symposium on Intelligent
Data Analysis. ‘s-Hertogenbosch, the Netherlands. https://doi.org/10.1007/978-3-030-01768-2_19
bibtex: '@inproceedings{Mohr_Wever_Hüllermeier, place={‘s-Hertogenbosch, the Netherlands},
title={Reduction Stumps for Multi-Class Classification}, DOI={10.1007/978-3-030-01768-2_19},
booktitle={Proceedings of the Symposium on Intelligent Data Analysis}, author={Mohr,
Felix and Wever, Marcel Dominik and Hüllermeier, Eyke} }'
chicago: Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Reduction Stumps
for Multi-Class Classification.” In Proceedings of the Symposium on Intelligent
Data Analysis. ‘s-Hertogenbosch, the Netherlands, n.d. https://doi.org/10.1007/978-3-030-01768-2_19.
ieee: F. Mohr, M. D. Wever, and E. Hüllermeier, “Reduction Stumps for Multi-Class
Classification,” in Proceedings of the Symposium on Intelligent Data Analysis,
‘s-Hertogenbosch, the Netherlands.
mla: Mohr, Felix, et al. “Reduction Stumps for Multi-Class Classification.” Proceedings
of the Symposium on Intelligent Data Analysis, doi:10.1007/978-3-030-01768-2_19.
short: 'F. Mohr, M.D. Wever, E. Hüllermeier, in: Proceedings of the Symposium on
Intelligent Data Analysis, ‘s-Hertogenbosch, the Netherlands, n.d.'
conference:
end_date: 2018-10-26
location: ‘s-Hertogenbosch, the Netherlands
name: Symposium on Intelligent Data Analysis
start_date: 2018-10-24
date_created: 2018-07-13T15:29:15Z
date_updated: 2022-01-06T06:59:25Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1007/978-3-030-01768-2_19
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:23:02Z
date_updated: 2018-11-06T15:23:02Z
file_id: '5385'
file_name: Mohr2018_Chapter_ReductionStumpsForMulti-classC.pdf
file_size: 1348768
relation: main_file
success: 1
file_date_updated: 2018-11-06T15:23:02Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/chapter/10.1007%2F978-3-030-01768-2_19
oa: '1'
place: ‘s-Hertogenbosch, the Netherlands
project:
- _id: '1'
name: SFB 901
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '3'
name: SFB 901 - Project Area B
publication: Proceedings of the Symposium on Intelligent Data Analysis
publication_status: accepted
quality_controlled: '1'
status: public
title: Reduction Stumps for Multi-Class Classification
type: conference
user_id: '49109'
year: '2018'
...
---
_id: '3852'
abstract:
- lang: eng
text: "In automated machine learning (AutoML), the process of engineering machine
learning applications with respect to a specific problem is (partially) automated.\r\nVarious
AutoML tools have already been introduced to provide out-of-the-box machine learning
functionality.\r\nMore specifically, by selecting machine learning algorithms
and optimizing their hyperparameters, these tools produce a machine learning pipeline
tailored to the problem at hand.\r\nExcept for TPOT, all of these tools restrict
the maximum number of processing steps of such a pipeline.\r\nHowever, as TPOT
follows an evolutionary approach, it suffers from performance issues when dealing
with larger datasets.\r\nIn this paper, we present an alternative approach leveraging
a hierarchical planning to configure machine learning pipelines that are unlimited
in length.\r\nWe evaluate our approach and find its performance to be competitive
with other AutoML tools, including TPOT."
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Mohr F, Hüllermeier E. ML-Plan for Unlimited-Length Machine Learning
Pipelines. In: ICML 2018 AutoML Workshop. ; 2018.'
apa: Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). ML-Plan for Unlimited-Length
Machine Learning Pipelines. In ICML 2018 AutoML Workshop. Stockholm, Sweden.
bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2018, title={ML-Plan for Unlimited-Length
Machine Learning Pipelines}, booktitle={ICML 2018 AutoML Workshop}, author={Wever,
Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2018} }'
chicago: Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “ML-Plan for Unlimited-Length
Machine Learning Pipelines.” In ICML 2018 AutoML Workshop, 2018.
ieee: M. D. Wever, F. Mohr, and E. Hüllermeier, “ML-Plan for Unlimited-Length Machine
Learning Pipelines,” in ICML 2018 AutoML Workshop, Stockholm, Sweden, 2018.
mla: Wever, Marcel Dominik, et al. “ML-Plan for Unlimited-Length Machine Learning
Pipelines.” ICML 2018 AutoML Workshop, 2018.
short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: ICML 2018 AutoML Workshop, 2018.'
conference:
end_date: 2018-07-15
location: Stockholm, Sweden
name: ICML 2018 AutoML Workshop
start_date: 2018-07-10
date_created: 2018-08-09T06:14:54Z
date_updated: 2022-01-06T06:59:46Z
ddc:
- '006'
department:
- _id: '355'
file:
- access_level: open_access
content_type: application/pdf
creator: wever
date_created: 2018-08-09T06:14:43Z
date_updated: 2018-08-09T06:14:43Z
file_id: '3853'
file_name: 38.pdf
file_size: 297811
relation: main_file
file_date_updated: 2018-08-09T06:14:43Z
has_accepted_license: '1'
keyword:
- automated machine learning
- complex pipelines
- hierarchical planning
language:
- iso: eng
main_file_link:
- url: https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxhdXRvbWwyMDE4aWNtbHxneDo3M2Q3MjUzYjViNDRhZTAx
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: ICML 2018 AutoML Workshop
quality_controlled: '1'
status: public
title: ML-Plan for Unlimited-Length Machine Learning Pipelines
type: conference
urn: '38527'
user_id: '49109'
year: '2018'
...
---
_id: '2109'
abstract:
- lang: eng
text: In multinomial classification, reduction techniques are commonly used to decompose
the original learning problem into several simpler problems. For example, by recursively
bisecting the original set of classes, so-called nested dichotomies define a set
of binary classification problems that are organized in the structure of a binary
tree. In contrast to the existing one-shot heuristics for constructing nested
dichotomies and motivated by recent work on algorithm configuration, we propose
a genetic algorithm for optimizing the structure of such dichotomies. A key component
of this approach is the proposed genetic representation that facilitates the application
of standard genetic operators, while still supporting the exchange of partial
solutions under recombination. We evaluate the approach in an extensive experimental
study, showing that it yields classifiers with superior generalization performance.
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Mohr F, Hüllermeier E. Ensembles of Evolved Nested Dichotomies for
Classification. In: Proceedings of the Genetic and Evolutionary Computation
Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto, Japan: ACM;
2018. doi:10.1145/3205455.3205562'
apa: 'Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). Ensembles of Evolved
Nested Dichotomies for Classification. In Proceedings of the Genetic and Evolutionary
Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto,
Japan: ACM. https://doi.org/10.1145/3205455.3205562'
bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2018, place={Kyoto, Japan}, title={Ensembles
of Evolved Nested Dichotomies for Classification}, DOI={10.1145/3205455.3205562},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2018, Kyoto, Japan, July 15-19, 2018}, publisher={ACM}, author={Wever, Marcel
Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2018} }'
chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Ensembles of
Evolved Nested Dichotomies for Classification.” In Proceedings of the Genetic
and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19,
2018. Kyoto, Japan: ACM, 2018. https://doi.org/10.1145/3205455.3205562.'
ieee: M. D. Wever, F. Mohr, and E. Hüllermeier, “Ensembles of Evolved Nested Dichotomies
for Classification,” in Proceedings of the Genetic and Evolutionary Computation
Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, Kyoto, Japan, 2018.
mla: Wever, Marcel Dominik, et al. “Ensembles of Evolved Nested Dichotomies for
Classification.” Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, 2018, doi:10.1145/3205455.3205562.
short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the Genetic and
Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018,
ACM, Kyoto, Japan, 2018.'
conference:
end_date: 2018-07-19
location: Kyoto, Japan
name: GECCO 2018
start_date: 2018-07-15
date_created: 2018-03-31T13:51:23Z
date_updated: 2022-01-06T06:54:45Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1145/3205455.3205562
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T14:33:54Z
date_updated: 2018-11-02T14:33:54Z
file_id: '5275'
file_name: p561-wever.pdf
file_size: 875404
relation: main_file
success: 1
file_date_updated: 2018-11-02T14:33:54Z
has_accepted_license: '1'
keyword:
- Classification
- Hierarchical Decomposition
- Indirect Encoding
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/citation.cfm?doid=3205455.3205562
oa: '1'
place: Kyoto, Japan
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO
2018, Kyoto, Japan, July 15-19, 2018
publication_status: published
publisher: ACM
status: public
title: Ensembles of Evolved Nested Dichotomies for Classification
type: conference
user_id: '33176'
year: '2018'
...
---
_id: '17713'
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Wever MD, Mohr F, Hüllermeier E. Automated Multi-Label Classification based
on ML-Plan. Published online 2018.
apa: Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). Automated Multi-Label
Classification based on ML-Plan. Arxiv.
bibtex: '@article{Wever_Mohr_Hüllermeier_2018, title={Automated Multi-Label Classification
based on ML-Plan}, publisher={Arxiv}, author={Wever, Marcel Dominik and Mohr,
Felix and Hüllermeier, Eyke}, year={2018} }'
chicago: Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automated Multi-Label
Classification Based on ML-Plan.” Arxiv, 2018.
ieee: M. D. Wever, F. Mohr, and E. Hüllermeier, “Automated Multi-Label Classification
based on ML-Plan.” Arxiv, 2018.
mla: Wever, Marcel Dominik, et al. Automated Multi-Label Classification Based
on ML-Plan. Arxiv, 2018.
short: M.D. Wever, F. Mohr, E. Hüllermeier, (2018).
date_created: 2020-08-07T11:38:10Z
date_updated: 2022-01-06T06:53:17Z
department:
- _id: '34'
- _id: '355'
- _id: '26'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/1811.04060.pdf
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publisher: Arxiv
status: public
title: Automated Multi-Label Classification based on ML-Plan
type: preprint
user_id: '5786'
year: '2018'
...
---
_id: '17714'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Mohr F, Wever MD, Hüllermeier E. Automated machine learning service composition.
Published online 2018.
apa: Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). Automated machine
learning service composition.
bibtex: '@article{Mohr_Wever_Hüllermeier_2018, title={Automated machine learning
service composition}, author={Mohr, Felix and Wever, Marcel Dominik and Hüllermeier,
Eyke}, year={2018} }'
chicago: Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Automated Machine
Learning Service Composition,” 2018.
ieee: F. Mohr, M. D. Wever, and E. Hüllermeier, “Automated machine learning service
composition.” 2018.
mla: Mohr, Felix, et al. Automated Machine Learning Service Composition.
2018.
short: F. Mohr, M.D. Wever, E. Hüllermeier, (2018).
date_created: 2020-08-07T11:40:13Z
date_updated: 2022-01-06T06:53:17Z
department:
- _id: '34'
- _id: '355'
- _id: '26'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/1809.00486.pdf
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
status: public
title: Automated machine learning service composition
type: preprint
user_id: '5786'
year: '2018'
...
---
_id: '5693'
author:
- first_name: Helena
full_name: Graf, Helena
id: '52640'
last_name: Graf
citation:
ama: Graf H. Ranking of Classification Algorithms in AutoML. Universität
Paderborn; 2018.
apa: Graf, H. (2018). Ranking of Classification Algorithms in AutoML. Universität
Paderborn.
bibtex: '@book{Graf_2018, title={Ranking of Classification Algorithms in AutoML},
publisher={Universität Paderborn}, author={Graf, Helena}, year={2018} }'
chicago: Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität
Paderborn, 2018.
ieee: H. Graf, Ranking of Classification Algorithms in AutoML. Universität
Paderborn, 2018.
mla: Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität
Paderborn, 2018.
short: H. Graf, Ranking of Classification Algorithms in AutoML, Universität Paderborn,
2018.
date_created: 2018-11-15T08:06:41Z
date_updated: 2022-01-06T07:02:35Z
department:
- _id: '355'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
title: Ranking of Classification Algorithms in AutoML
type: bachelorsthesis
user_id: '33176'
year: '2018'
...
---
_id: '5936'
author:
- first_name: Manuel
full_name: Scheibl, Manuel
last_name: Scheibl
citation:
ama: Scheibl M. Learning about Learning Curves from Dataset Properties. Universität
Paderborn; 2018.
apa: Scheibl, M. (2018). Learning about learning curves from dataset properties.
Universität Paderborn.
bibtex: '@book{Scheibl_2018, title={Learning about learning curves from dataset
properties}, publisher={Universität Paderborn}, author={Scheibl, Manuel}, year={2018}
}'
chicago: Scheibl, Manuel. Learning about Learning Curves from Dataset Properties.
Universität Paderborn, 2018.
ieee: M. Scheibl, Learning about learning curves from dataset properties.
Universität Paderborn, 2018.
mla: Scheibl, Manuel. Learning about Learning Curves from Dataset Properties.
Universität Paderborn, 2018.
short: M. Scheibl, Learning about Learning Curves from Dataset Properties, Universität
Paderborn, 2018.
date_created: 2018-11-28T10:29:53Z
date_updated: 2022-01-06T07:02:47Z
department:
- _id: '355'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
title: Learning about learning curves from dataset properties
type: bachelorsthesis
user_id: '477'
year: '2018'
...
---
_id: '6423'
author:
- first_name: Dirk
full_name: Schäfer, Dirk
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad
Ranking. In: Discovery Science. Cham: Springer International Publishing;
2018:161-175. doi:10.1007/978-3-030-01771-2_11'
apa: 'Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement
Learning Using Dyad Ranking. In Discovery Science (pp. 161–175). Cham:
Springer International Publishing. https://doi.org/10.1007/978-3-030-01771-2_11'
bibtex: '@inbook{Schäfer_Hüllermeier_2018, place={Cham}, title={Preference-Based
Reinforcement Learning Using Dyad Ranking}, DOI={10.1007/978-3-030-01771-2_11},
booktitle={Discovery Science}, publisher={Springer International Publishing},
author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={161–175} }'
chicago: 'Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” In Discovery Science, 161–75. Cham: Springer International
Publishing, 2018. https://doi.org/10.1007/978-3-030-01771-2_11.'
ieee: 'D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using
Dyad Ranking,” in Discovery Science, Cham: Springer International Publishing,
2018, pp. 161–175.'
mla: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” Discovery Science, Springer International Publishing,
2018, pp. 161–75, doi:10.1007/978-3-030-01771-2_11.
short: 'D. Schäfer, E. Hüllermeier, in: Discovery Science, Springer International
Publishing, Cham, 2018, pp. 161–175.'
date_created: 2018-12-20T15:52:03Z
date_updated: 2022-01-06T07:03:04Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1007/978-3-030-01771-2_11
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2019-01-11T11:03:50Z
date_updated: 2019-01-11T11:03:50Z
file_id: '6623'
file_name: Schäfer-Hüllermeier2018_Chapter_Preference-BasedReinforcementL.pdf
file_size: 458972
relation: main_file
success: 1
file_date_updated: 2019-01-11T11:03:50Z
has_accepted_license: '1'
language:
- iso: eng
page: 161-175
place: Cham
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: Discovery Science
publication_identifier:
isbn:
- '9783030017705'
- '9783030017712'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer International Publishing
status: public
title: Preference-Based Reinforcement Learning Using Dyad Ranking
type: book_chapter
user_id: '49109'
year: '2018'
...
---
_id: '10591'
alternative_title:
- Manifesto from Dagstuhl Perspectives Workshop 16151
citation:
ama: Abiteboul S, Arenas M, Barceló P, et al., eds. Research Directions for Principles
of Data Management. Vol 7.; 2018:1-29.
apa: Abiteboul, S., Arenas, M., Barceló, P., Bienvenu, M., Calvanese, D., David,
C., … Yi, K. (Eds.). (2018). Research Directions for Principles of Data Management
(Vol. 7, pp. 1–29).
bibtex: '@book{Abiteboul_Arenas_Barceló_Bienvenu_Calvanese_David_Hull_Hüllermeier_Kimelfeld_Libkin_et
al._2018, title={Research Directions for Principles of Data Management}, volume={7},
number={1}, year={2018}, pages={1–29} }'
chicago: Abiteboul, S., M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David,
R. Hull, et al., eds. Research Directions for Principles of Data Management.
Vol. 7, 2018.
ieee: S. Abiteboul et al., Eds., Research Directions for Principles of
Data Management, vol. 7, no. 1. 2018, pp. 1–29.
mla: Abiteboul, S., et al., editors. Research Directions for Principles of Data
Management. Vol. 7, no. 1, 2018, pp. 1–29.
short: S. Abiteboul, M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David,
R. Hull, E. Hüllermeier, B. Kimelfeld, L. Libkin, W. Martens, T. Milo, F. Murlak,
F. Neven, M. Ortiz, T. Schwentick, J. Stoyanovich, J. Su, D. Suciu, V. Vianu,
K. Yi, eds., Research Directions for Principles of Data Management, 2018.
date_created: 2019-07-09T15:58:12Z
date_updated: 2022-01-06T06:50:45Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
editor:
- first_name: S.
full_name: Abiteboul, S.
last_name: Abiteboul
- first_name: M.
full_name: Arenas, M.
last_name: Arenas
- first_name: P.
full_name: Barceló, P.
last_name: Barceló
- first_name: M.
full_name: Bienvenu, M.
last_name: Bienvenu
- first_name: D.
full_name: Calvanese, D.
last_name: Calvanese
- first_name: C.
full_name: David, C.
last_name: David
- first_name: R.
full_name: Hull, R.
last_name: Hull
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: B.
full_name: Kimelfeld, B.
last_name: Kimelfeld
- first_name: L.
full_name: Libkin, L.
last_name: Libkin
- first_name: W.
full_name: Martens, W.
last_name: Martens
- first_name: T.
full_name: Milo, T.
last_name: Milo
- first_name: F.
full_name: Murlak, F.
last_name: Murlak
- first_name: F.
full_name: Neven, F.
last_name: Neven
- first_name: M.
full_name: Ortiz, M.
last_name: Ortiz
- first_name: T.
full_name: Schwentick, T.
last_name: Schwentick
- first_name: J.
full_name: Stoyanovich, J.
last_name: Stoyanovich
- first_name: J.
full_name: Su, J.
last_name: Su
- first_name: D.
full_name: Suciu, D.
last_name: Suciu
- first_name: V.
full_name: Vianu, V.
last_name: Vianu
- first_name: K.
full_name: Yi, K.
last_name: Yi
intvolume: ' 7'
issue: '1'
language:
- iso: eng
page: 1-29
status: public
title: Research Directions for Principles of Data Management
type: conference_editor
user_id: '49109'
volume: 7
year: '2018'
...
---
_id: '10783'
author:
- first_name: Ines
full_name: Couso, Ines
last_name: Couso
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Couso I, Hüllermeier E. Statistical Inference for Incomplete Ranking Data:
A Comparison of two likelihood-based estimators. In: Mostaghim S, Nürnberger A,
Borgelt C, eds. Frontiers in Computational Intelligence. Springer; 2018:31-46.'
apa: 'Couso, I., & Hüllermeier, E. (2018). Statistical Inference for Incomplete
Ranking Data: A Comparison of two likelihood-based estimators. In S. Mostaghim,
A. Nürnberger, & C. Borgelt (Eds.), Frontiers in Computational Intelligence
(pp. 31–46). Springer.'
bibtex: '@inbook{Couso_Hüllermeier_2018, title={Statistical Inference for Incomplete
Ranking Data: A Comparison of two likelihood-based estimators}, booktitle={Frontiers
in Computational Intelligence}, publisher={Springer}, author={Couso, Ines and
Hüllermeier, Eyke}, editor={Mostaghim, Sanaz and Nürnberger, Andreas and Borgelt,
ChristianEditors}, year={2018}, pages={31–46} }'
chicago: 'Couso, Ines, and Eyke Hüllermeier. “Statistical Inference for Incomplete
Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Frontiers
in Computational Intelligence, edited by Sanaz Mostaghim, Andreas Nürnberger,
and Christian Borgelt, 31–46. Springer, 2018.'
ieee: 'I. Couso and E. Hüllermeier, “Statistical Inference for Incomplete Ranking
Data: A Comparison of two likelihood-based estimators,” in Frontiers in Computational
Intelligence, S. Mostaghim, A. Nürnberger, and C. Borgelt, Eds. Springer,
2018, pp. 31–46.'
mla: 'Couso, Ines, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking
Data: A Comparison of Two Likelihood-Based Estimators.” Frontiers in Computational
Intelligence, edited by Sanaz Mostaghim et al., Springer, 2018, pp. 31–46.'
short: 'I. Couso, E. Hüllermeier, in: S. Mostaghim, A. Nürnberger, C. Borgelt (Eds.),
Frontiers in Computational Intelligence, Springer, 2018, pp. 31–46.'
date_created: 2019-07-10T15:39:00Z
date_updated: 2022-01-06T06:50:50Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
editor:
- first_name: Sanaz
full_name: Mostaghim, Sanaz
last_name: Mostaghim
- first_name: Andreas
full_name: Nürnberger, Andreas
last_name: Nürnberger
- first_name: Christian
full_name: Borgelt, Christian
last_name: Borgelt
language:
- iso: eng
page: 31-46
publication: Frontiers in Computational Intelligence
publisher: Springer
status: public
title: 'Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based
estimators'
type: book_chapter
user_id: '49109'
year: '2018'
...
---
_id: '16038'
author:
- first_name: D.
full_name: Schäfer, D.
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Schäfer D, Hüllermeier E. Dyad ranking using Plackett-Luce models based on
joint feature representations. Machine Learning. 2018;107(5):903-941.
apa: Schäfer, D., & Hüllermeier, E. (2018). Dyad ranking using Plackett-Luce
models based on joint feature representations. Machine Learning, 107(5),
903–941.
bibtex: '@article{Schäfer_Hüllermeier_2018, title={Dyad ranking using Plackett-Luce
models based on joint feature representations}, volume={107}, number={5}, journal={Machine
Learning}, author={Schäfer, D. and Hüllermeier, Eyke}, year={2018}, pages={903–941}
}'
chicago: 'Schäfer, D., and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models
Based on Joint Feature Representations.” Machine Learning 107, no. 5 (2018):
903–41.'
ieee: D. Schäfer and E. Hüllermeier, “Dyad ranking using Plackett-Luce models based
on joint feature representations,” Machine Learning, vol. 107, no. 5, pp.
903–941, 2018.
mla: Schäfer, D., and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models
Based on Joint Feature Representations.” Machine Learning, vol. 107, no.
5, 2018, pp. 903–41.
short: D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941.
date_created: 2020-02-24T15:59:19Z
date_updated: 2022-01-06T06:52:42Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
intvolume: ' 107'
issue: '5'
language:
- iso: eng
page: 903-941
publication: Machine Learning
status: public
title: Dyad ranking using Plackett-Luce models based on joint feature representations
type: journal_article
user_id: '49109'
volume: 107
year: '2018'
...
---
_id: '10145'
author:
- first_name: Mohsen
full_name: Ahmadi Fahandar, Mohsen
last_name: Ahmadi Fahandar
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Ahmadi Fahandar M, Hüllermeier E. Learning to Rank Based on Analogical Reasoning.
In: Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI). ; 2018:2951-2958.'
apa: Ahmadi Fahandar, M., & Hüllermeier, E. (2018). Learning to Rank Based on
Analogical Reasoning. In Proc. 32 nd AAAI Conference on Artificial Intelligence
(AAAI) (pp. 2951–2958).
bibtex: '@inproceedings{Ahmadi Fahandar_Hüllermeier_2018, title={Learning to Rank
Based on Analogical Reasoning}, booktitle={Proc. 32 nd AAAI Conference on Artificial
Intelligence (AAAI)}, author={Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke},
year={2018}, pages={2951–2958} }'
chicago: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based
on Analogical Reasoning.” In Proc. 32 Nd AAAI Conference on Artificial Intelligence
(AAAI), 2951–58, 2018.
ieee: M. Ahmadi Fahandar and E. Hüllermeier, “Learning to Rank Based on Analogical
Reasoning,” in Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI),
2018, pp. 2951–2958.
mla: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical
Reasoning.” Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI),
2018, pp. 2951–58.
short: 'M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. 32 Nd AAAI Conference on Artificial
Intelligence (AAAI), 2018, pp. 2951–2958.'
date_created: 2019-06-07T08:49:33Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 2951-2958
publication: Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI)
status: public
title: Learning to Rank Based on Analogical Reasoning
type: conference
user_id: '49109'
year: '2018'
...
---
_id: '10148'
author:
- first_name: Adil
full_name: El Mesaoudi-Paul, Adil
last_name: El Mesaoudi-Paul
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Robert
full_name: Busa-Fekete, Robert
last_name: Busa-Fekete
citation:
ama: 'El Mesaoudi-Paul A, Hüllermeier E, Busa-Fekete R. Ranking Distributions based
on Noisy Sorting. In: Proc. 35th Int. Conference on Machine Learning (ICML).
Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn. Verlagsschriftenreihe
des Heinz Nixdorf Instituts, Paderborn; 2018:3469-3477.'
apa: El Mesaoudi-Paul, A., Hüllermeier, E., & Busa-Fekete, R. (2018). Ranking
Distributions based on Noisy Sorting. Proc. 35th Int. Conference on Machine
Learning (ICML), 3469–3477.
bibtex: '@inproceedings{El Mesaoudi-Paul_Hüllermeier_Busa-Fekete_2018, series={Verlagsschriftenreihe
des Heinz Nixdorf Instituts, Paderborn}, title={Ranking Distributions based on
Noisy Sorting}, booktitle={Proc. 35th Int. Conference on Machine Learning (ICML)},
publisher={Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn}, author={El
Mesaoudi-Paul, Adil and Hüllermeier, Eyke and Busa-Fekete, Robert}, year={2018},
pages={3469–3477}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts,
Paderborn} }'
chicago: El Mesaoudi-Paul, Adil, Eyke Hüllermeier, and Robert Busa-Fekete. “Ranking
Distributions Based on Noisy Sorting.” In Proc. 35th Int. Conference on Machine
Learning (ICML), 3469–77. Verlagsschriftenreihe Des Heinz Nixdorf Instituts,
Paderborn. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
ieee: A. El Mesaoudi-Paul, E. Hüllermeier, and R. Busa-Fekete, “Ranking Distributions
based on Noisy Sorting,” in Proc. 35th Int. Conference on Machine Learning
(ICML), 2018, pp. 3469–3477.
mla: El Mesaoudi-Paul, Adil, et al. “Ranking Distributions Based on Noisy Sorting.”
Proc. 35th Int. Conference on Machine Learning (ICML), Verlagsschriftenreihe
des Heinz Nixdorf Instituts, Paderborn, 2018, pp. 3469–77.
short: 'A. El Mesaoudi-Paul, E. Hüllermeier, R. Busa-Fekete, in: Proc. 35th Int.
Conference on Machine Learning (ICML), Verlagsschriftenreihe des Heinz Nixdorf
Instituts, Paderborn, 2018, pp. 3469–3477.'
date_created: 2019-06-07T09:02:37Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 3469-3477
publication: Proc. 35th Int. Conference on Machine Learning (ICML)
publisher: Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn
series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn
status: public
title: Ranking Distributions based on Noisy Sorting
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10149'
author:
- first_name: M.
full_name: Hesse, M.
last_name: Hesse
- first_name: J.
full_name: Timmermann, J.
last_name: Timmermann
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Ansgar
full_name: Trächtler, Ansgar
last_name: Trächtler
citation:
ama: 'Hesse M, Timmermann J, Hüllermeier E, Trächtler A. A Reinforcement Learning
Strategy for the Swing-Up of the Double Pendulum on a Cart. In: Proc. 4th Int.
Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected
Systems in Products and Production, Procedia Manufacturing 24. ; 2018:15-20.'
apa: 'Hesse, M., Timmermann, J., Hüllermeier, E., & Trächtler, A. (2018). A
Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.
Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible
and Connected Systems in Products and Production, Procedia Manufacturing 24,
15–20.'
bibtex: '@inproceedings{Hesse_Timmermann_Hüllermeier_Trächtler_2018, title={A Reinforcement
Learning Strategy for the Swing-Up of the Double Pendulum on a Cart}, booktitle={Proc.
4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and
Connected Systems in Products and Production, Procedia Manufacturing 24}, author={Hesse,
M. and Timmermann, J. and Hüllermeier, Eyke and Trächtler, Ansgar}, year={2018},
pages={15–20} }'
chicago: 'Hesse, M., J. Timmermann, Eyke Hüllermeier, and Ansgar Trächtler. “A Reinforcement
Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.” In Proc.
4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and
Connected Systems in Products and Production, Procedia Manufacturing 24, 15–20,
2018.'
ieee: 'M. Hesse, J. Timmermann, E. Hüllermeier, and A. Trächtler, “A Reinforcement
Learning Strategy for the Swing-Up of the Double Pendulum on a Cart,” in Proc.
4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and
Connected Systems in Products and Production, Procedia Manufacturing 24, 2018,
pp. 15–20.'
mla: 'Hesse, M., et al. “A Reinforcement Learning Strategy for the Swing-Up of the
Double Pendulum on a Cart.” Proc. 4th Int. Conference on System-Integrated
Intelligence: Intelligent, Flexible and Connected Systems in Products and Production,
Procedia Manufacturing 24, 2018, pp. 15–20.'
short: 'M. Hesse, J. Timmermann, E. Hüllermeier, A. Trächtler, in: Proc. 4th Int.
Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected
Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.'
date_created: 2019-06-07T09:10:51Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 15-20
publication: 'Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent,
Flexible and Connected Systems in Products and Production, Procedia Manufacturing
24'
status: public
title: A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on
a Cart
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10152'
author:
- first_name: E.Loza
full_name: Mencia, E.Loza
last_name: Mencia
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: M.
full_name: Rapp, M.
last_name: Rapp
citation:
ama: 'Mencia EL, Fürnkranz J, Hüllermeier E, Rapp M. Learning interpretable rules
for multi-label classification. In: Jair Escalante H, Escalera S, Guyon I, et
al., eds. Explainable and Interpretable Models in Computer Vision and Machine
Learning. The Springer Series on Challenges in Machine Learning. Springer;
2018:81-113.'
apa: Mencia, E. L., Fürnkranz, J., Hüllermeier, E., & Rapp, M. (2018). Learning
interpretable rules for multi-label classification. In H. Jair Escalante, S. Escalera,
I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, & M. A. J. van Gerven (Eds.),
Explainable and Interpretable Models in Computer Vision and Machine Learning
(pp. 81–113). Springer.
bibtex: '@inbook{Mencia_Fürnkranz_Hüllermeier_Rapp_2018, series={The Springer Series
on Challenges in Machine Learning}, title={Learning interpretable rules for multi-label
classification}, booktitle={Explainable and Interpretable Models in Computer Vision
and Machine Learning}, publisher={Springer}, author={Mencia, E.Loza and Fürnkranz,
J. and Hüllermeier, Eyke and Rapp, M.}, editor={Jair Escalante, H. and Escalera,
S. and Guyon, I. and Baro, X. and Güclüütürk, Y. and Güclü, U. and van Gerven,
M.A.J.Editors}, year={2018}, pages={81–113}, collection={The Springer Series on
Challenges in Machine Learning} }'
chicago: Mencia, E.Loza, J. Fürnkranz, Eyke Hüllermeier, and M. Rapp. “Learning
Interpretable Rules for Multi-Label Classification.” In Explainable and Interpretable
Models in Computer Vision and Machine Learning, edited by H. Jair Escalante,
S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M.A.J. van Gerven,
81–113. The Springer Series on Challenges in Machine Learning. Springer, 2018.
ieee: E. L. Mencia, J. Fürnkranz, E. Hüllermeier, and M. Rapp, “Learning interpretable
rules for multi-label classification,” in Explainable and Interpretable Models
in Computer Vision and Machine Learning, H. Jair Escalante, S. Escalera, I.
Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M. A. J. van Gerven, Eds. Springer,
2018, pp. 81–113.
mla: Mencia, E. Loz., et al. “Learning Interpretable Rules for Multi-Label Classification.”
Explainable and Interpretable Models in Computer Vision and Machine Learning,
edited by H. Jair Escalante et al., Springer, 2018, pp. 81–113.
short: 'E.L. Mencia, J. Fürnkranz, E. Hüllermeier, M. Rapp, in: H. Jair Escalante,
S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, M.A.J. van Gerven (Eds.),
Explainable and Interpretable Models in Computer Vision and Machine Learning,
Springer, 2018, pp. 81–113.'
date_created: 2019-06-07T09:17:56Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
editor:
- first_name: H.
full_name: Jair Escalante, H.
last_name: Jair Escalante
- first_name: S.
full_name: Escalera, S.
last_name: Escalera
- first_name: I.
full_name: Guyon, I.
last_name: Guyon
- first_name: X.
full_name: Baro, X.
last_name: Baro
- first_name: Y.
full_name: Güclüütürk, Y.
last_name: Güclüütürk
- first_name: U.
full_name: Güclü, U.
last_name: Güclü
- first_name: M.A.J.
full_name: van Gerven, M.A.J.
last_name: van Gerven
language:
- iso: eng
page: 81-113
publication: Explainable and Interpretable Models in Computer Vision and Machine Learning
publisher: Springer
series_title: The Springer Series on Challenges in Machine Learning
status: public
title: Learning interpretable rules for multi-label classification
type: book_chapter
user_id: '49109'
year: '2018'
...
---
_id: '10181'
author:
- first_name: Vu-Linh
full_name: Nguyen, Vu-Linh
last_name: Nguyen
- first_name: Sebastian
full_name: Destercke, Sebastian
last_name: Destercke
- first_name: M.-H.
full_name: Masson, M.-H.
last_name: Masson
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Nguyen V-L, Destercke S, Masson M-H, Hüllermeier E. Reliable Multi-class Classification
based on Pairwise Epistemic and Aleatoric Uncertainty. In: Proc. 27th Int.Joint
Conference on Artificial Intelligence (IJCAI). ; 2018:5089-5095.'
apa: Nguyen, V.-L., Destercke, S., Masson, M.-H., & Hüllermeier, E. (2018).
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric
Uncertainty. Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI),
5089–5095.
bibtex: '@inproceedings{Nguyen_Destercke_Masson_Hüllermeier_2018, title={Reliable
Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty},
booktitle={Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI)},
author={Nguyen, Vu-Linh and Destercke, Sebastian and Masson, M.-H. and Hüllermeier,
Eyke}, year={2018}, pages={5089–5095} }'
chicago: Nguyen, Vu-Linh, Sebastian Destercke, M.-H. Masson, and Eyke Hüllermeier.
“Reliable Multi-Class Classification Based on Pairwise Epistemic and Aleatoric
Uncertainty.” In Proc. 27th Int.Joint Conference on Artificial Intelligence
(IJCAI), 5089–95, 2018.
ieee: V.-L. Nguyen, S. Destercke, M.-H. Masson, and E. Hüllermeier, “Reliable Multi-class
Classification based on Pairwise Epistemic and Aleatoric Uncertainty,” in Proc.
27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.
mla: Nguyen, Vu-Linh, et al. “Reliable Multi-Class Classification Based on Pairwise
Epistemic and Aleatoric Uncertainty.” Proc. 27th Int.Joint Conference on Artificial
Intelligence (IJCAI), 2018, pp. 5089–95.
short: 'V.-L. Nguyen, S. Destercke, M.-H. Masson, E. Hüllermeier, in: Proc. 27th
Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.'
date_created: 2019-06-07T12:31:20Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 5089-5095
publication: Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI)
status: public
title: Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric
Uncertainty
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10184'
author:
- first_name: Dirk
full_name: Schäfer, Dirk
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad
Ranking. In: Proc. 21st Int. Conference on Discovery Science (DS). ; 2018:161-175.'
apa: Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement Learning
Using Dyad Ranking. Proc. 21st Int. Conference on Discovery Science (DS),
161–175.
bibtex: '@inproceedings{Schäfer_Hüllermeier_2018, title={Preference-Based Reinforcement
Learning Using Dyad Ranking}, booktitle={Proc. 21st Int. Conference on Discovery
Science (DS)}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={161–175}
}'
chicago: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” In Proc. 21st Int. Conference on Discovery Science (DS),
161–75, 2018.
ieee: D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using
Dyad Ranking,” in Proc. 21st Int. Conference on Discovery Science (DS),
2018, pp. 161–175.
mla: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” Proc. 21st Int. Conference on Discovery Science (DS),
2018, pp. 161–75.
short: 'D. Schäfer, E. Hüllermeier, in: Proc. 21st Int. Conference on Discovery
Science (DS), 2018, pp. 161–175.'
date_created: 2019-06-07T12:33:58Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 161-175
publication: Proc. 21st Int. Conference on Discovery Science (DS)
status: public
title: Preference-Based Reinforcement Learning Using Dyad Ranking
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10276'
author:
- first_name: Dirk
full_name: Schäfer, Dirk
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Schäfer D, Hüllermeier E. Dyad Ranking Using Plackett-Luce Models based on
joint feature representations. Machine Learning. 2018;107(5):903-941.
apa: Schäfer, D., & Hüllermeier, E. (2018). Dyad Ranking Using Plackett-Luce
Models based on joint feature representations. Machine Learning, 107(5),
903–941.
bibtex: '@article{Schäfer_Hüllermeier_2018, title={Dyad Ranking Using Plackett-Luce
Models based on joint feature representations}, volume={107}, number={5}, journal={Machine
Learning}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={903–941}
}'
chicago: 'Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce
Models Based on Joint Feature Representations.” Machine Learning 107, no.
5 (2018): 903–41.'
ieee: D. Schäfer and E. Hüllermeier, “Dyad Ranking Using Plackett-Luce Models based
on joint feature representations,” Machine Learning, vol. 107, no. 5, pp.
903–941, 2018.
mla: Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models
Based on Joint Feature Representations.” Machine Learning, vol. 107, no.
5, 2018, pp. 903–41.
short: D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941.
date_created: 2019-06-19T14:58:10Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
intvolume: ' 107'
issue: '5'
language:
- iso: eng
page: 903-941
publication: Machine Learning
status: public
title: Dyad Ranking Using Plackett-Luce Models based on joint feature representations
type: journal_article
user_id: '49109'
volume: 107
year: '2018'
...
---
_id: '1379'
author:
- first_name: Nina
full_name: Seemann, Nina
id: '65408'
last_name: Seemann
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
- first_name: Marie-Luis
full_name: Merten, Marie-Luis
last_name: Merten
- first_name: Doris
full_name: Tophinke, Doris
id: '16277'
last_name: Tophinke
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Seemann N, Geierhos M, Merten M-L, Tophinke D, Wever MD, Hüllermeier E. Supporting
the Cognitive Process in Annotation Tasks. In: Eckart K, Schlechtweg D, eds. Postersession
Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft.
; 2018.'
apa: Seemann, N., Geierhos, M., Merten, M.-L., Tophinke, D., Wever, M. D., &
Hüllermeier, E. (2018). Supporting the Cognitive Process in Annotation Tasks.
In K. Eckart & D. Schlechtweg (Eds.), Postersession Computerlinguistik
der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft.
bibtex: '@inproceedings{Seemann_Geierhos_Merten_Tophinke_Wever_Hüllermeier_2018,
title={Supporting the Cognitive Process in Annotation Tasks}, booktitle={Postersession
Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft},
author={Seemann, Nina and Geierhos, Michaela and Merten, Marie-Luis and Tophinke,
Doris and Wever, Marcel Dominik and Hüllermeier, Eyke}, editor={Eckart, Kerstin and
Schlechtweg, Dominik }, year={2018} }'
chicago: Seemann, Nina, Michaela Geierhos, Marie-Luis Merten, Doris Tophinke, Marcel
Dominik Wever, and Eyke Hüllermeier. “Supporting the Cognitive Process in Annotation
Tasks.” In Postersession Computerlinguistik der 40. Jahrestagung der Deutschen
Gesellschaft für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg,
2018.
ieee: N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M. D. Wever, and E. Hüllermeier,
“Supporting the Cognitive Process in Annotation Tasks,” in Postersession Computerlinguistik
der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, Stuttgart,
Germany, 2018.
mla: Seemann, Nina, et al. “Supporting the Cognitive Process in Annotation Tasks.”
Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft
für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg,
2018.
short: 'N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M.D. Wever, E. Hüllermeier,
in: K. Eckart, D. Schlechtweg (Eds.), Postersession Computerlinguistik der 40.
Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, 2018.'
conference:
end_date: 2018-03-09
location: Stuttgart, Germany
name: Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft
für Sprachwissenschaft
start_date: 2018-03-07
date_created: 2018-03-19T15:23:25Z
date_updated: 2023-01-09T14:56:56Z
ddc:
- '410'
department:
- _id: '36'
- _id: '1'
- _id: '579'
- _id: '115'
- _id: '355'
- _id: '115'
editor:
- first_name: 'Kerstin '
full_name: 'Eckart, Kerstin '
last_name: Eckart
- first_name: 'Dominik '
full_name: 'Schlechtweg, Dominik '
last_name: Schlechtweg
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:32:38Z
date_updated: 2018-11-06T15:32:38Z
file_id: '5389'
file_name: 2018_dgfs-cl-poster-seemann-etal.pdf
file_size: 158928
relation: main_file
success: 1
file_date_updated: 2018-11-06T15:32:38Z
has_accepted_license: '1'
language:
- iso: ger
main_file_link:
- open_access: '1'
url: https://www.dgfs2018.uni-stuttgart.de/programm/postersession/programm-cl-postersession/2018_dgfs-cl-poster-seemann-etal.pdf
oa: '1'
project:
- _id: '39'
name: InterGramm
publication: Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft
für Sprachwissenschaft
publication_status: published
quality_controlled: '1'
status: public
title: Supporting the Cognitive Process in Annotation Tasks
type: conference_abstract
user_id: '16277'
year: '2018'
...
---
_id: '24152'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Shalabh
full_name: Bhatnagar, Shalabh
last_name: Bhatnagar
citation:
ama: Ramaswamy A, Bhatnagar S. Analysis of gradient descent methods with nondiminishing
bounded errors. IEEE Transactions on Automatic Control. 2017;63(5):1465-1471.
apa: Ramaswamy, A., & Bhatnagar, S. (2017). Analysis of gradient descent methods
with nondiminishing bounded errors. IEEE Transactions on Automatic Control,
63(5), 1465–1471.
bibtex: '@article{Ramaswamy_Bhatnagar_2017, title={Analysis of gradient descent
methods with nondiminishing bounded errors}, volume={63}, number={5}, journal={IEEE
Transactions on Automatic Control}, publisher={IEEE}, author={Ramaswamy, Arunselvan
and Bhatnagar, Shalabh}, year={2017}, pages={1465–1471} }'
chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent
Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic
Control 63, no. 5 (2017): 1465–71.'
ieee: A. Ramaswamy and S. Bhatnagar, “Analysis of gradient descent methods with
nondiminishing bounded errors,” IEEE Transactions on Automatic Control,
vol. 63, no. 5, pp. 1465–1471, 2017.
mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent
Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic
Control, vol. 63, no. 5, IEEE, 2017, pp. 1465–71.
short: A. Ramaswamy, S. Bhatnagar, IEEE Transactions on Automatic Control 63 (2017)
1465–1471.
date_created: 2021-09-10T10:19:40Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
extern: '1'
intvolume: ' 63'
issue: '5'
language:
- iso: eng
page: 1465-1471
publication: IEEE Transactions on Automatic Control
publisher: IEEE
status: public
title: Analysis of gradient descent methods with nondiminishing bounded errors
type: journal_article
user_id: '66937'
volume: 63
year: '2017'
...
---
_id: '24153'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Shalabh
full_name: Bhatnagar, Shalabh
last_name: Bhatnagar
citation:
ama: Ramaswamy A, Bhatnagar S. A generalization of the Borkar-Meyn theorem for stochastic
recursive inclusions. Mathematics of Operations Research. 2017;42(3):648-661.
apa: Ramaswamy, A., & Bhatnagar, S. (2017). A generalization of the Borkar-Meyn
theorem for stochastic recursive inclusions. Mathematics of Operations Research,
42(3), 648–661.
bibtex: '@article{Ramaswamy_Bhatnagar_2017, title={A generalization of the Borkar-Meyn
theorem for stochastic recursive inclusions}, volume={42}, number={3}, journal={Mathematics
of Operations Research}, publisher={INFORMS}, author={Ramaswamy, Arunselvan and
Bhatnagar, Shalabh}, year={2017}, pages={648–661} }'
chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the
Borkar-Meyn Theorem for Stochastic Recursive Inclusions.” Mathematics of Operations
Research 42, no. 3 (2017): 648–61.'
ieee: A. Ramaswamy and S. Bhatnagar, “A generalization of the Borkar-Meyn theorem
for stochastic recursive inclusions,” Mathematics of Operations Research,
vol. 42, no. 3, pp. 648–661, 2017.
mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the Borkar-Meyn
Theorem for Stochastic Recursive Inclusions.” Mathematics of Operations Research,
vol. 42, no. 3, INFORMS, 2017, pp. 648–61.
short: A. Ramaswamy, S. Bhatnagar, Mathematics of Operations Research 42 (2017)
648–661.
date_created: 2021-09-10T10:21:02Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
extern: '1'
intvolume: ' 42'
issue: '3'
language:
- iso: eng
page: 648-661
publication: Mathematics of Operations Research
publisher: INFORMS
status: public
title: A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions
type: journal_article
user_id: '66937'
volume: 42
year: '2017'
...
---
_id: '3325'
author:
- first_name: Vitalik
full_name: Melnikov, Vitalik
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics. In: Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing;
2017. doi:10.5445/KSP/1000074341'
apa: 'Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics. In Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing.
https://doi.org/10.5445/KSP/1000074341'
bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure
of Nested Dichotomies: A Comparison of Two Heuristics}, DOI={10.5445/KSP/1000074341},
booktitle={Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23.
- 24. November 2017}, publisher={KIT Scientific Publishing}, author={Melnikov,
Vitalik and Hüllermeier, Eyke}, year={2017} }'
chicago: 'Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of
Nested Dichotomies: A Comparison of Two Heuristics.” In Proceedings. 27. Workshop
Computational Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific
Publishing, 2017. https://doi.org/10.5445/KSP/1000074341.'
ieee: 'V. Melnikov and E. Hüllermeier, “Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics,” in Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017, 2017.'
mla: 'Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics.” Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing,
2017, doi:10.5445/KSP/1000074341.'
short: 'V. Melnikov, E. Hüllermeier, in: Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017.'
date_created: 2018-06-25T08:14:49Z
date_updated: 2022-01-06T06:59:10Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.5445/KSP/1000074341
file:
- access_level: closed
content_type: application/pdf
creator: melnikov
date_created: 2018-11-30T09:47:59Z
date_updated: 2018-11-30T09:47:59Z
file_id: '5987'
file_name: main.pdf
file_size: 1829552
relation: main_file
success: 1
file_date_updated: 2018-11-30T09:47:59Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '3'
name: SFB 901 - Project Area B
- _id: '1'
name: SFB 901
publication: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. -
24. November 2017
publisher: KIT Scientific Publishing
status: public
title: 'Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics'
type: conference
user_id: '15504'
year: '2017'
...
---
_id: '115'
abstract:
- lang: eng
text: 'Whenever customers have to decide between different instances of the same
product, they are interested in buying the best product. In contrast, companies
are interested in reducing the construction effort (and usually as a consequence
thereof, the quality) to gain profit. The described setting is widely known as
opposed preferences in quality of the product and also applies to the context
of service-oriented computing. In general, service-oriented computing emphasizes
the construction of large software systems out of existing services, where services
are small and self-contained pieces of software that adhere to a specified interface.
Several implementations of the same interface are considered as several instances
of the same service. Thereby, customers are interested in buying the best service
implementation for their service composition wrt. to metrics, such as costs, energy,
memory consumption, or execution time. One way to ensure the service quality is
to employ certificates, which can come in different kinds: Technical certificates
proving correctness can be automatically constructed by the service provider and
again be automatically checked by the user. Digital certificates allow proof of
the integrity of a product. Other certificates might be rolled out if service
providers follow a good software construction principle, which is checked in annual
audits. Whereas all of these certificates are handled differently in service markets,
what they have in common is that they influence the buying decisions of customers.
In this paper, we review state-of-the-art developments in certification with respect
to service-oriented computing. We not only discuss how certificates are constructed
and handled in service-oriented computing but also review the effects of certificates
on the market from an economic perspective.'
author:
- first_name: Marie-Christine
full_name: Jakobs, Marie-Christine
last_name: Jakobs
- first_name: Julia
full_name: Krämer, Julia
last_name: Krämer
- first_name: Dirk
full_name: van Straaten, Dirk
id: '10311'
last_name: van Straaten
- first_name: Theodor
full_name: Lettmann, Theodor
id: '315'
last_name: Lettmann
orcid: 0000-0001-5859-2457
citation:
ama: 'Jakobs M-C, Krämer J, van Straaten D, Lettmann T. Certification Matters for
Service Markets. In: Marcelo De Barros, Janusz Klink,Tadeus Uhl TP, ed. The
Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION).
; 2017:7-12.'
apa: Jakobs, M.-C., Krämer, J., van Straaten, D., & Lettmann, T. (2017). Certification
Matters for Service Markets. In T. P. Marcelo De Barros, Janusz Klink,Tadeus Uhl
(Ed.), The Ninth International Conferences on Advanced Service Computing (SERVICE
COMPUTATION) (pp. 7–12).
bibtex: '@inproceedings{Jakobs_Krämer_van Straaten_Lettmann_2017, title={Certification
Matters for Service Markets}, booktitle={The Ninth International Conferences on
Advanced Service Computing (SERVICE COMPUTATION)}, author={Jakobs, Marie-Christine
and Krämer, Julia and van Straaten, Dirk and Lettmann, Theodor}, editor={Marcelo
De Barros, Janusz Klink,Tadeus Uhl, Thomas PrinzEditor}, year={2017}, pages={7–12}
}'
chicago: Jakobs, Marie-Christine, Julia Krämer, Dirk van Straaten, and Theodor Lettmann.
“Certification Matters for Service Markets.” In The Ninth International Conferences
on Advanced Service Computing (SERVICE COMPUTATION), edited by Thomas Prinz
Marcelo De Barros, Janusz Klink,Tadeus Uhl, 7–12, 2017.
ieee: M.-C. Jakobs, J. Krämer, D. van Straaten, and T. Lettmann, “Certification Matters
for Service Markets,” in The Ninth International Conferences on Advanced Service
Computing (SERVICE COMPUTATION), 2017, pp. 7–12.
mla: Jakobs, Marie-Christine, et al. “Certification Matters for Service Markets.”
The Ninth International Conferences on Advanced Service Computing (SERVICE
COMPUTATION), edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus
Uhl, 2017, pp. 7–12.
short: 'M.-C. Jakobs, J. Krämer, D. van Straaten, T. Lettmann, in: T.P. Marcelo
De Barros, Janusz Klink,Tadeus Uhl (Ed.), The Ninth International Conferences
on Advanced Service Computing (SERVICE COMPUTATION), 2017, pp. 7–12.'
date_created: 2017-10-17T12:41:14Z
date_updated: 2022-01-06T06:51:02Z
ddc:
- '040'
department:
- _id: '77'
- _id: '355'
- _id: '179'
editor:
- first_name: Thomas Prinz
full_name: Marcelo De Barros, Janusz Klink,Tadeus Uhl, Thomas Prinz
last_name: Marcelo De Barros, Janusz Klink,Tadeus Uhl
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T13:04:12Z
date_updated: 2018-03-21T13:04:12Z
file_id: '1564'
file_name: 115-JakobsKraemerVanStraatenLettmann2017.pdf
file_size: 133531
relation: main_file
success: 1
file_date_updated: 2018-03-21T13:04:12Z
has_accepted_license: '1'
language:
- iso: eng
page: 7-12
project:
- _id: '1'
name: SFB 901
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '12'
name: SFB 901 - Subproject B4
- _id: '8'
name: SFB 901 - Subproject A4
- _id: '2'
name: SFB 901 - Project Area A
- _id: '3'
name: SFB 901 - Project Area B
publication: The Ninth International Conferences on Advanced Service Computing (SERVICE
COMPUTATION)
status: public
title: Certification Matters for Service Markets
type: conference
user_id: '477'
year: '2017'
...
---
_id: '1158'
abstract:
- lang: eng
text: In this paper, we present the annotation challenges we have encountered when
working on a historical language that was undergoing elaboration processes. We
especially focus on syntactic ambiguity and gradience in Middle Low German, which
causes uncertainty to some extent. Since current annotation tools consider construction
contexts and the dynamics of the grammaticalization only partially, we plan to
extend CorA – a web-based annotation tool for historical and other non-standard
language data – to capture elaboration phenomena and annotator unsureness. Moreover,
we seek to interactively learn morphological as well as syntactic annotations.
author:
- first_name: Nina
full_name: Seemann, Nina
id: '65408'
last_name: Seemann
- first_name: Marie-Luis
full_name: Merten, Marie-Luis
last_name: Merten
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
- first_name: Doris
full_name: Tophinke, Doris
last_name: Tophinke
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
citation:
ama: 'Seemann N, Merten M-L, Geierhos M, Tophinke D, Hüllermeier E. Annotation Challenges
for Reconstructing the Structural Elaboration of Middle Low German. In: Proceedings
of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage,
Social Sciences, Humanities and Literature. Stroudsburg, PA, USA: Association
for Computational Linguistics (ACL); 2017:40-45. doi:10.18653/v1/W17-2206'
apa: 'Seemann, N., Merten, M.-L., Geierhos, M., Tophinke, D., & Hüllermeier,
E. (2017). Annotation Challenges for Reconstructing the Structural Elaboration
of Middle Low German. In Proceedings of the Joint SIGHUM Workshop on Computational
Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
(pp. 40–45). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL).
https://doi.org/10.18653/v1/W17-2206'
bibtex: '@inproceedings{Seemann_Merten_Geierhos_Tophinke_Hüllermeier_2017, place={Stroudsburg,
PA, USA}, title={Annotation Challenges for Reconstructing the Structural Elaboration
of Middle Low German}, DOI={10.18653/v1/W17-2206},
booktitle={Proceedings of the Joint SIGHUM Workshop on Computational Linguistics
for Cultural Heritage, Social Sciences, Humanities and Literature}, publisher={Association
for Computational Linguistics (ACL)}, author={Seemann, Nina and Merten, Marie-Luis
and Geierhos, Michaela and Tophinke, Doris and Hüllermeier, Eyke}, year={2017},
pages={40–45} }'
chicago: 'Seemann, Nina, Marie-Luis Merten, Michaela Geierhos, Doris Tophinke, and
Eyke Hüllermeier. “Annotation Challenges for Reconstructing the Structural Elaboration
of Middle Low German.” In Proceedings of the Joint SIGHUM Workshop on Computational
Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature,
40–45. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL),
2017. https://doi.org/10.18653/v1/W17-2206.'
ieee: N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, and E. Hüllermeier, “Annotation
Challenges for Reconstructing the Structural Elaboration of Middle Low German,”
in Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for
Cultural Heritage, Social Sciences, Humanities and Literature, Vancouver,
BC, Canada, 2017, pp. 40–45.
mla: Seemann, Nina, et al. “Annotation Challenges for Reconstructing the Structural
Elaboration of Middle Low German.” Proceedings of the Joint SIGHUM Workshop
on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities
and Literature, Association for Computational Linguistics (ACL), 2017, pp.
40–45, doi:10.18653/v1/W17-2206.
short: 'N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, E. Hüllermeier, in:
Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural
Heritage, Social Sciences, Humanities and Literature, Association for Computational
Linguistics (ACL), Stroudsburg, PA, USA, 2017, pp. 40–45.'
conference:
end_date: 2017-08-04
location: Vancouver, BC, Canada
name: Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage,
Social Sciences, Humanities and Literature (LaTeCH-CLfL 2017)
start_date: 2017-07-31
date_created: 2018-01-31T15:32:33Z
date_updated: 2022-01-06T06:51:03Z
department:
- _id: '36'
- _id: '579'
- _id: '115'
- _id: '355'
- _id: '615'
doi: 10.18653/v1/W17-2206
language:
- iso: eng
page: 40-45
place: Stroudsburg, PA, USA
project:
- _id: '39'
name: InterGramm
publication: Proceedings of the Joint SIGHUM Workshop on Computational Linguistics
for Cultural Heritage, Social Sciences, Humanities and Literature
publication_status: published
publisher: Association for Computational Linguistics (ACL)
quality_controlled: '1'
status: public
title: Annotation Challenges for Reconstructing the Structural Elaboration of Middle
Low German
type: conference
user_id: '13929'
year: '2017'
...
---
_id: '5694'
author:
- first_name: Nino Noel
full_name: Schnitker, Nino Noel
last_name: Schnitker
citation:
ama: Schnitker NN. Genetischer Algorithmus zur Erstellung von Ensembles von Nested
Dichotomies. Universität Paderborn; 2017.
apa: Schnitker, N. N. (2017). Genetischer Algorithmus zur Erstellung von Ensembles
von Nested Dichotomies. Universität Paderborn.
bibtex: '@book{Schnitker_2017, title={Genetischer Algorithmus zur Erstellung von
Ensembles von Nested Dichotomies}, publisher={Universität Paderborn}, author={Schnitker,
Nino Noel}, year={2017} }'
chicago: Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles
von Nested Dichotomies. Universität Paderborn, 2017.
ieee: N. N. Schnitker, Genetischer Algorithmus zur Erstellung von Ensembles von
Nested Dichotomies. Universität Paderborn, 2017.
mla: Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles
von Nested Dichotomies. Universität Paderborn, 2017.
short: N.N. Schnitker, Genetischer Algorithmus zur Erstellung von Ensembles von
Nested Dichotomies, Universität Paderborn, 2017.
date_created: 2018-11-15T08:10:48Z
date_updated: 2022-01-06T07:02:35Z
department:
- _id: '355'
language:
- iso: ger
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
title: Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies
type: bachelorsthesis
user_id: '477'
year: '2017'
...
---
_id: '5722'
author:
- first_name: Pritha
full_name: Gupta, Pritha
last_name: Gupta
- first_name: Alexander
full_name: Hetzer, Alexander
id: '38209'
last_name: Hetzer
- first_name: Tanja
full_name: Tornede, Tanja
last_name: Tornede
- first_name: Sebastian
full_name: Gottschalk, Sebastian
last_name: Gottschalk
- first_name: Andreas
full_name: Kornelsen, Andreas
last_name: Kornelsen
- first_name: Sebastian
full_name: Osterbrink, Sebastian
last_name: Osterbrink
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
citation:
ama: 'Gupta P, Hetzer A, Tornede T, et al. jPL: A Java-based Software Framework
for Preference Learning. In: ; 2017.'
apa: 'Gupta, P., Hetzer, A., Tornede, T., Gottschalk, S., Kornelsen, A., Osterbrink,
S., … Hüllermeier, E. (2017). jPL: A Java-based Software Framework for Preference
Learning. Presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock.'
bibtex: '@inproceedings{Gupta_Hetzer_Tornede_Gottschalk_Kornelsen_Osterbrink_Pfannschmidt_Hüllermeier_2017,
title={jPL: A Java-based Software Framework for Preference Learning}, author={Gupta,
Pritha and Hetzer, Alexander and Tornede, Tanja and Gottschalk, Sebastian and
Kornelsen, Andreas and Osterbrink, Sebastian and Pfannschmidt, Karlson and Hüllermeier,
Eyke}, year={2017} }'
chicago: 'Gupta, Pritha, Alexander Hetzer, Tanja Tornede, Sebastian Gottschalk,
Andreas Kornelsen, Sebastian Osterbrink, Karlson Pfannschmidt, and Eyke Hüllermeier.
“JPL: A Java-Based Software Framework for Preference Learning,” 2017.'
ieee: 'P. Gupta et al., “jPL: A Java-based Software Framework for Preference
Learning,” presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock,
2017.'
mla: 'Gupta, Pritha, et al. JPL: A Java-Based Software Framework for Preference
Learning. 2017.'
short: 'P. Gupta, A. Hetzer, T. Tornede, S. Gottschalk, A. Kornelsen, S. Osterbrink,
K. Pfannschmidt, E. Hüllermeier, in: 2017.'
conference:
end_date: 13.09.2017
location: Rostock
name: 'WDA 2017 Workshops: KDML, FGWM, IR, and FGDB'
start_date: 11.09.2017
date_created: 2018-11-19T07:32:31Z
date_updated: 2022-01-06T07:02:37Z
department:
- _id: '355'
extern: '1'
language:
- iso: eng
status: public
title: 'jPL: A Java-based Software Framework for Preference Learning'
type: conference_abstract
user_id: '38209'
year: '2017'
...
---
_id: '5724'
author:
- first_name: Alexander
full_name: Hetzer, Alexander
id: '38209'
last_name: Hetzer
- first_name: Tanja
full_name: Tornede, Tanja
last_name: Tornede
citation:
ama: Hetzer A, Tornede T. Solving the Container Pre-Marshalling Problem Using
Reinforcement Learning and Structured Output Prediction. Universität Paderborn;
2017.
apa: Hetzer, A., & Tornede, T. (2017). Solving the Container Pre-Marshalling
Problem using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn.
bibtex: '@book{Hetzer_Tornede_2017, title={Solving the Container Pre-Marshalling
Problem using Reinforcement Learning and Structured Output Prediction}, publisher={Universität
Paderborn}, author={Hetzer, Alexander and Tornede, Tanja}, year={2017} }'
chicago: Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling
Problem Using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn, 2017.
ieee: A. Hetzer and T. Tornede, Solving the Container Pre-Marshalling Problem
using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn, 2017.
mla: Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling
Problem Using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn, 2017.
short: A. Hetzer, T. Tornede, Solving the Container Pre-Marshalling Problem Using
Reinforcement Learning and Structured Output Prediction, Universität Paderborn,
2017.
date_created: 2018-11-19T07:49:13Z
date_updated: 2022-01-06T07:02:37Z
department:
- _id: '355'
- _id: '199'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Kevin
full_name: Tierney, Kevin
last_name: Tierney
title: Solving the Container Pre-Marshalling Problem using Reinforcement Learning
and Structured Output Prediction
type: mastersthesis
user_id: '477'
year: '2017'
...
---
_id: '71'
abstract:
- lang: eng
text: Today, software verification tools have reached the maturity to be used for
large scale programs. Different tools perform differently well on varying code.
A software developer is hence faced with the problem of choosing a tool appropriate
for her program at hand. A ranking of tools on programs could facilitate the choice.
Such rankings can, however, so far only be obtained by running all considered
tools on the program.In this paper, we present a machine learning approach to
predicting rankings of tools on programs. The method builds upon so-called label
ranking algorithms, which we complement with appropriate kernels providing a similarity
measure for programs. Our kernels employ a graph representation for software source
code that mixes elements of control flow and program dependence graphs with abstract
syntax trees. Using data sets from the software verification competition SV-COMP,
we demonstrate our rank prediction technique to generalize well and achieve a
rather high predictive accuracy (rank correlation > 0.6).
author:
- first_name: Mike
full_name: Czech, Mike
last_name: Czech
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Marie-Christine
full_name: Jakobs, Marie-Christine
last_name: Jakobs
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: 'Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software
Verification Tools. In: Proceedings of the 3rd International Workshop on Software
Analytics. SWAN’17. ; 2017:23-26. doi:10.1145/3121257.3121262'
apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting
Rankings of Software Verification Tools. In Proceedings of the 3rd International
Workshop on Software Analytics (pp. 23–26). https://doi.org/10.1145/3121257.3121262
bibtex: '@inproceedings{Czech_Hüllermeier_Jakobs_Wehrheim_2017, series={SWAN’17},
title={Predicting Rankings of Software Verification Tools}, DOI={10.1145/3121257.3121262},
booktitle={Proceedings of the 3rd International Workshop on Software Analytics},
author={Czech, Mike and Hüllermeier, Eyke and Jakobs, Marie-Christine and Wehrheim,
Heike}, year={2017}, pages={23–26}, collection={SWAN’17} }'
chicago: Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim.
“Predicting Rankings of Software Verification Tools.” In Proceedings of the
3rd International Workshop on Software Analytics, 23–26. SWAN’17, 2017. https://doi.org/10.1145/3121257.3121262.
ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, “Predicting Rankings
of Software Verification Tools,” in Proceedings of the 3rd International Workshop
on Software Analytics, 2017, pp. 23–26.
mla: Czech, Mike, et al. “Predicting Rankings of Software Verification Tools.” Proceedings
of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26,
doi:10.1145/3121257.3121262.
short: 'M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proceedings of
the 3rd International Workshop on Software Analytics, 2017, pp. 23–26.'
date_created: 2017-10-17T12:41:05Z
date_updated: 2022-01-06T07:03:28Z
ddc:
- '000'
department:
- _id: '355'
- _id: '77'
doi: 10.1145/3121257.3121262
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T14:24:29Z
date_updated: 2018-11-02T14:24:29Z
file_id: '5271'
file_name: fsews17swan-swanmain1.pdf
file_size: 822383
relation: main_file
success: 1
file_date_updated: 2018-11-02T14:24:29Z
has_accepted_license: '1'
language:
- iso: eng
page: 23-26
project:
- _id: '1'
name: SFB 901
- _id: '12'
name: SFB 901 - Subprojekt B4
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '3'
name: SFB 901 - Project Area B
- _id: '11'
name: SFB 901 - Subproject B3
publication: Proceedings of the 3rd International Workshop on Software Analytics
series_title: SWAN'17
status: public
title: Predicting Rankings of Software Verification Tools
type: conference
user_id: '15504'
year: '2017'
...
---
_id: '72'
abstract:
- lang: eng
text: 'Software verification competitions, such as the annual SV-COMP, evaluate
software verification tools with respect to their effectivity and efficiency.
Typically, the outcome of a competition is a (possibly category-specific) ranking
of the tools. For many applications, such as building portfolio solvers, it would
be desirable to have an idea of the (relative) performance of verification tools
on a given verification task beforehand, i.e., prior to actually running all tools
on the task.In this paper, we present a machine learning approach to predicting
rankings of tools on verification tasks. The method builds upon so-called label
ranking algorithms, which we complement with appropriate kernels providing a similarity
measure for verification tasks. Our kernels employ a graph representation for
software source code that mixes elements of control flow and program dependence
graphs with abstract syntax trees. Using data sets from SV-COMP, we demonstrate
our rank prediction technique to generalize well and achieve a rather high predictive
accuracy. In particular, our method outperforms a recently proposed feature-based
approach of Demyanova et al. (when applied to rank predictions). '
author:
- first_name: Mike
full_name: Czech, Mike
last_name: Czech
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Marie-Christine
full_name: Jakobs, Marie-Christine
last_name: Jakobs
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software
Verification Competitions.; 2017.
apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting
Rankings of Software Verification Competitions.
bibtex: '@book{Czech_Hüllermeier_Jakobs_Wehrheim_2017, title={Predicting Rankings
of Software Verification Competitions}, author={Czech, Mike and Hüllermeier, Eyke
and Jakobs, Marie-Christine and Wehrheim, Heike}, year={2017} }'
chicago: Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim.
Predicting Rankings of Software Verification Competitions, 2017.
ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, Predicting Rankings
of Software Verification Competitions. 2017.
mla: Czech, Mike, et al. Predicting Rankings of Software Verification Competitions.
2017.
short: M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Predicting Rankings
of Software Verification Competitions, 2017.
date_created: 2017-10-17T12:41:05Z
date_updated: 2022-01-06T07:03:29Z
ddc:
- '000'
department:
- _id: '77'
- _id: '355'
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-11-21T10:50:11Z
date_updated: 2018-11-21T10:50:11Z
file_id: '5782'
file_name: "Predicting Rankings of So\x81ware Verification Competitions.pdf"
file_size: 869984
relation: main_file
success: 1
file_date_updated: 2018-11-21T10:50:11Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '11'
name: SFB 901 - Subprojekt B3
- _id: '12'
name: SFB 901 - Subprojekt B4
- _id: '3'
name: SFB 901 - Project Area B
status: public
title: Predicting Rankings of Software Verification Competitions
type: report
user_id: '15504'
year: '2017'
...
---
_id: '10589'
author:
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Encyclopedia of Machine
Learning and Data Mining. ; 2017:1000-1005.'
apa: Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In Encyclopedia
of Machine Learning and Data Mining (pp. 1000–1005).
bibtex: '@inbook{Fürnkranz_Hüllermeier_2017, title={Preference Learning}, booktitle={Encyclopedia
of Machine Learning and Data Mining}, author={Fürnkranz, J. and Hüllermeier, Eyke},
year={2017}, pages={1000–1005} }'
chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia
of Machine Learning and Data Mining, 1000–1005, 2017.
ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia
of Machine Learning and Data Mining, 2017, pp. 1000–1005.
mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia
of Machine Learning and Data Mining, 2017, pp. 1000–05.
short: 'J. Fürnkranz, E. Hüllermeier, in: Encyclopedia of Machine Learning and Data
Mining, 2017, pp. 1000–1005.'
date_created: 2019-07-09T15:37:09Z
date_updated: 2022-01-06T06:50:45Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 1000-1005
publication: Encyclopedia of Machine Learning and Data Mining
status: public
title: Preference Learning
type: encyclopedia_article
user_id: '49109'
year: '2017'
...
---
_id: '10784'
author:
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds.
Encyclopedia of Machine Learning and Data Mining. Vol 107. Springer; 2017:1000-1005.'
apa: Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In C. Sammut
& G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining
(Vol. 107, pp. 1000–1005). Springer.
bibtex: '@inbook{Fürnkranz_Hüllermeier_2017, title={Preference Learning}, volume={107},
booktitle={Encyclopedia of Machine Learning and Data Mining}, publisher={Springer},
author={Fürnkranz, J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors},
year={2017}, pages={1000–1005} }'
chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, 107:1000–1005.
Springer, 2017.
ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia
of Machine Learning and Data Mining, vol. 107, C. Sammut and G. I. Webb, Eds.
Springer, 2017, pp. 1000–1005.
mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, vol.
107, Springer, 2017, pp. 1000–05.
short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia
of Machine Learning and Data Mining, Springer, 2017, pp. 1000–1005.'
date_created: 2019-07-10T15:44:32Z
date_updated: 2022-01-06T06:50:50Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: C.
full_name: Sammut, C.
last_name: Sammut
- first_name: G.I.
full_name: Webb, G.I.
last_name: Webb
intvolume: ' 107'
language:
- iso: eng
page: 1000-1005
publication: Encyclopedia of Machine Learning and Data Mining
publisher: Springer
status: public
title: Preference Learning
type: book_chapter
user_id: '49109'
volume: 107
year: '2017'
...
---
_id: '1180'
abstract:
- lang: eng
text: These days, there is a strong rise in the needs for machine learning applications,
requiring an automation of machine learning engineering which is referred to as
AutoML. In AutoML the selection, composition and parametrization of machine learning
algorithms is automated and tailored to a specific problem, resulting in a machine
learning pipeline. Current approaches reduce the AutoML problem to optimization
of hyperparameters. Based on recursive task networks, in this paper we present
one approach from the field of automated planning and one evolutionary optimization
approach. Instead of simply parametrizing a given pipeline, this allows for structure
optimization of machine learning pipelines, as well. We evaluate the two approaches
in an extensive evaluation, finding both approaches to have their strengths in
different areas. Moreover, the two approaches outperform the state-of-the-art
tool Auto-WEKA in many settings.
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierachical Planning
Versus Evolutionary Optimization. In: 27th Workshop Computational Intelligence.
Dortmund; 2017.'
apa: 'Wever, M. D., Mohr, F., & Hüllermeier, E. (2017). Automatic Machine Learning:
Hierachical Planning Versus Evolutionary Optimization. In 27th Workshop Computational
Intelligence. Dortmund.'
bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2017, place={Dortmund}, title={Automatic
Machine Learning: Hierachical Planning Versus Evolutionary Optimization}, booktitle={27th
Workshop Computational Intelligence}, author={Wever, Marcel Dominik and Mohr,
Felix and Hüllermeier, Eyke}, year={2017} }'
chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automatic Machine
Learning: Hierachical Planning Versus Evolutionary Optimization.” In 27th Workshop
Computational Intelligence. Dortmund, 2017.'
ieee: 'M. D. Wever, F. Mohr, and E. Hüllermeier, “Automatic Machine Learning: Hierachical
Planning Versus Evolutionary Optimization,” in 27th Workshop Computational
Intelligence, Dortmund, 2017.'
mla: 'Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning
Versus Evolutionary Optimization.” 27th Workshop Computational Intelligence,
2017.'
short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence,
Dortmund, 2017.'
conference:
end_date: 2017-11-24
location: Dortmund
name: 27th Workshop Computational Intelligence
start_date: 2017-11-23
date_created: 2018-02-22T07:19:18Z
date_updated: 2022-01-06T06:51:09Z
ddc:
- '000'
department:
- _id: '355'
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:28:09Z
date_updated: 2018-11-06T15:28:09Z
file_id: '5387'
file_name: CI Workshop AutoML.pdf
file_size: 323589
relation: main_file
success: 1
file_date_updated: 2018-11-06T15:28:09Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://publikationen.bibliothek.kit.edu/1000074341/4643874
oa: '1'
place: Dortmund
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: 27th Workshop Computational Intelligence
publication_status: published
status: public
title: 'Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization'
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '15397'
author:
- first_name: Vitaly
full_name: Melnikov, Vitaly
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Optimizing the structure of nested dichotomies.
A comparison of two heuristics. In: Hoffmann F, Hüllermeier E, Mikut R, eds. In
Proceedings 27th Workshop Computational Intelligence, Dortmund Germany. KIT
Scientific Publishing; 2017:1-12.'
apa: Melnikov, V., & Hüllermeier, E. (2017). Optimizing the structure of nested
dichotomies. A comparison of two heuristics. In F. Hoffmann, E. Hüllermeier, &
R. Mikut (Eds.), in Proceedings 27th Workshop Computational Intelligence, Dortmund
Germany (pp. 1–12). KIT Scientific Publishing.
bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the structure
of nested dichotomies. A comparison of two heuristics}, booktitle={in Proceedings
27th Workshop Computational Intelligence, Dortmund Germany}, publisher={KIT Scientific
Publishing}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, editor={Hoffmann,
F. and Hüllermeier, Eyke and Mikut, R.Editors}, year={2017}, pages={1–12} }'
chicago: Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies. A Comparison of Two Heuristics.” In In Proceedings 27th Workshop
Computational Intelligence, Dortmund Germany, edited by F. Hoffmann, Eyke
Hüllermeier, and R. Mikut, 1–12. KIT Scientific Publishing, 2017.
ieee: V. Melnikov and E. Hüllermeier, “Optimizing the structure of nested dichotomies.
A comparison of two heuristics,” in in Proceedings 27th Workshop Computational
Intelligence, Dortmund Germany, 2017, pp. 1–12.
mla: Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies. A Comparison of Two Heuristics.” In Proceedings 27th Workshop
Computational Intelligence, Dortmund Germany, edited by F. Hoffmann et al.,
KIT Scientific Publishing, 2017, pp. 1–12.
short: 'V. Melnikov, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.),
In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, KIT
Scientific Publishing, 2017, pp. 1–12.'
date_created: 2019-12-19T15:48:38Z
date_updated: 2022-01-06T06:52:22Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: F.
full_name: Hoffmann, F.
last_name: Hoffmann
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: R.
full_name: Mikut, R.
last_name: Mikut
language:
- iso: eng
page: 1-12
publication: in Proceedings 27th Workshop Computational Intelligence, Dortmund Germany
publisher: KIT Scientific Publishing
status: public
title: Optimizing the structure of nested dichotomies. A comparison of two heuristics
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '15399'
author:
- first_name: M.
full_name: Czech, M.
last_name: Czech
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: M.C.
full_name: Jacobs, M.C.
last_name: Jacobs
- first_name: Heike
full_name: Wehrheim, Heike
last_name: Wehrheim
citation:
ama: 'Czech M, Hüllermeier E, Jacobs MC, Wehrheim H. Predicting rankings of software
verification tools. In: In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT,
International Workshop on Software Analytics (SWAN 2017), Paderborn Germany.
; 2017.'
apa: Czech, M., Hüllermeier, E., Jacobs, M. C., & Wehrheim, H. (2017). Predicting
rankings of software verification tools. In in Proceedings ESEC/FSE Workshops
2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017),
Paderborn Germany.
bibtex: '@inproceedings{Czech_Hüllermeier_Jacobs_Wehrheim_2017, title={Predicting
rankings of software verification tools}, booktitle={in Proceedings ESEC/FSE Workshops
2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017),
Paderborn Germany}, author={Czech, M. and Hüllermeier, Eyke and Jacobs, M.C. and
Wehrheim, Heike}, year={2017} }'
chicago: Czech, M., Eyke Hüllermeier, M.C. Jacobs, and Heike Wehrheim. “Predicting
Rankings of Software Verification Tools.” In In Proceedings ESEC/FSE Workshops
2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017),
Paderborn Germany, 2017.
ieee: M. Czech, E. Hüllermeier, M. C. Jacobs, and H. Wehrheim, “Predicting rankings
of software verification tools,” in in Proceedings ESEC/FSE Workshops 2017
- 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn
Germany, 2017.
mla: Czech, M., et al. “Predicting Rankings of Software Verification Tools.” In
Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop
on Software Analytics (SWAN 2017), Paderborn Germany, 2017.
short: 'M. Czech, E. Hüllermeier, M.C. Jacobs, H. Wehrheim, in: In Proceedings ESEC/FSE
Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics
(SWAN 2017), Paderborn Germany, 2017.'
date_created: 2019-12-19T15:59:42Z
date_updated: 2022-01-06T06:52:22Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: in Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International
Workshop on Software Analytics (SWAN 2017), Paderborn Germany
status: public
title: Predicting rankings of software verification tools
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '15110'
author:
- first_name: Ines
full_name: Couso, Ines
last_name: Couso
- first_name: D.
full_name: Dubois, D.
last_name: Dubois
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Couso I, Dubois D, Hüllermeier E. Maximum likelihood estimation and coarse
data. In: In Proceedings SUM 2017, 11th International Conference on Scalable
Uncertainty Management, Granada, Spain. Springer; 2017:3-16.'
apa: Couso, I., Dubois, D., & Hüllermeier, E. (2017). Maximum likelihood estimation
and coarse data. In in Proceedings SUM 2017, 11th International Conference
on Scalable Uncertainty Management, Granada, Spain (pp. 3–16). Springer.
bibtex: '@inproceedings{Couso_Dubois_Hüllermeier_2017, title={Maximum likelihood
estimation and coarse data}, booktitle={in Proceedings SUM 2017, 11th International
Conference on Scalable Uncertainty Management, Granada, Spain}, publisher={Springer},
author={Couso, Ines and Dubois, D. and Hüllermeier, Eyke}, year={2017}, pages={3–16}
}'
chicago: Couso, Ines, D. Dubois, and Eyke Hüllermeier. “Maximum Likelihood Estimation
and Coarse Data.” In In Proceedings SUM 2017, 11th International Conference
on Scalable Uncertainty Management, Granada, Spain, 3–16. Springer, 2017.
ieee: I. Couso, D. Dubois, and E. Hüllermeier, “Maximum likelihood estimation and
coarse data,” in in Proceedings SUM 2017, 11th International Conference on
Scalable Uncertainty Management, Granada, Spain, 2017, pp. 3–16.
mla: Couso, Ines, et al. “Maximum Likelihood Estimation and Coarse Data.” In
Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management,
Granada, Spain, Springer, 2017, pp. 3–16.
short: 'I. Couso, D. Dubois, E. Hüllermeier, in: In Proceedings SUM 2017, 11th International
Conference on Scalable Uncertainty Management, Granada, Spain, Springer, 2017,
pp. 3–16.'
date_created: 2019-11-21T16:38:39Z
date_updated: 2022-01-06T06:52:15Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 3-16
publication: in Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty
Management, Granada, Spain
publisher: Springer
status: public
title: Maximum likelihood estimation and coarse data
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10204'
author:
- first_name: Ralph
full_name: Ewerth, Ralph
last_name: Ewerth
- first_name: M.
full_name: Springstein, M.
last_name: Springstein
- first_name: E.
full_name: Müller, E.
last_name: Müller
- first_name: A.
full_name: Balz, A.
last_name: Balz
- first_name: J.
full_name: Gehlhaar, J.
last_name: Gehlhaar
- first_name: T.
full_name: Naziyok, T.
last_name: Naziyok
- first_name: K.
full_name: Dembczynski, K.
last_name: Dembczynski
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Ewerth R, Springstein M, Müller E, et al. Estimating relative depth in single
images via rankboost. In: Proc. IEEE Int. Conf. on Multimedia and Expo (ICME
2017). ; 2017:919-924.'
apa: Ewerth, R., Springstein, M., Müller, E., Balz, A., Gehlhaar, J., Naziyok, T.,
… Hüllermeier, E. (2017). Estimating relative depth in single images via rankboost.
In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017) (pp. 919–924).
bibtex: '@inproceedings{Ewerth_Springstein_Müller_Balz_Gehlhaar_Naziyok_Dembczynski_Hüllermeier_2017,
title={Estimating relative depth in single images via rankboost}, booktitle={Proc.
IEEE Int. Conf. on Multimedia and Expo (ICME 2017)}, author={Ewerth, Ralph and
Springstein, M. and Müller, E. and Balz, A. and Gehlhaar, J. and Naziyok, T. and
Dembczynski, K. and Hüllermeier, Eyke}, year={2017}, pages={919–924} }'
chicago: Ewerth, Ralph, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok,
K. Dembczynski, and Eyke Hüllermeier. “Estimating Relative Depth in Single Images
via Rankboost.” In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017),
919–24, 2017.
ieee: R. Ewerth et al., “Estimating relative depth in single images via rankboost,”
in Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp.
919–924.
mla: Ewerth, Ralph, et al. “Estimating Relative Depth in Single Images via Rankboost.”
Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp. 919–24.
short: 'R. Ewerth, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok,
K. Dembczynski, E. Hüllermeier, in: Proc. IEEE Int. Conf. on Multimedia and Expo
(ICME 2017), 2017, pp. 919–924.'
date_created: 2019-06-07T15:18:24Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 919-924
publication: Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017)
status: public
title: Estimating relative depth in single images via rankboost
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10205'
author:
- first_name: Mohsen
full_name: Ahmadi Fahandar, Mohsen
last_name: Ahmadi Fahandar
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Ines
full_name: Couso, Ines
last_name: Couso
citation:
ama: 'Ahmadi Fahandar M, Hüllermeier E, Couso I. Statistical Inference for Incomplete
Ranking Data: The Case of Rank-Dependent Coarsening. In: Proc. 34th Int. Conf.
on Machine Learning (ICML 2017). ; 2017:1078-1087.'
apa: 'Ahmadi Fahandar, M., Hüllermeier, E., & Couso, I. (2017). Statistical
Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening.
In Proc. 34th Int. Conf. on Machine Learning (ICML 2017) (pp. 1078–1087).'
bibtex: '@inproceedings{Ahmadi Fahandar_Hüllermeier_Couso_2017, title={Statistical
Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening},
booktitle={Proc. 34th Int. Conf. on Machine Learning (ICML 2017)}, author={Ahmadi
Fahandar, Mohsen and Hüllermeier, Eyke and Couso, Ines}, year={2017}, pages={1078–1087}
}'
chicago: 'Ahmadi Fahandar, Mohsen, Eyke Hüllermeier, and Ines Couso. “Statistical
Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening.”
In Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 1078–87, 2017.'
ieee: 'M. Ahmadi Fahandar, E. Hüllermeier, and I. Couso, “Statistical Inference
for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening,” in Proc.
34th Int. Conf. on Machine Learning (ICML 2017), 2017, pp. 1078–1087.'
mla: 'Ahmadi Fahandar, Mohsen, et al. “Statistical Inference for Incomplete Ranking
Data: The Case of Rank-Dependent Coarsening.” Proc. 34th Int. Conf. on Machine
Learning (ICML 2017), 2017, pp. 1078–87.'
short: 'M. Ahmadi Fahandar, E. Hüllermeier, I. Couso, in: Proc. 34th Int. Conf.
on Machine Learning (ICML 2017), 2017, pp. 1078–1087.'
date_created: 2019-06-07T15:22:01Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 1078-1087
publication: Proc. 34th Int. Conf. on Machine Learning (ICML 2017)
status: public
title: 'Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening'
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10206'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Theodor
full_name: Lettmann, Theodor
id: '315'
last_name: Lettmann
orcid: 0000-0001-5859-2457
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Mohr F, Lettmann T, Hüllermeier E. Planning with Independent Task Networks.
In: Proc. 40th Annual German Conference on Advances in Artificial Intelligence
(KI 2017). ; 2017:193-206. doi:10.1007/978-3-319-67190-1_15'
apa: Mohr, F., Lettmann, T., & Hüllermeier, E. (2017). Planning with Independent
Task Networks. In Proc. 40th Annual German Conference on Advances in Artificial
Intelligence (KI 2017) (pp. 193–206). https://doi.org/10.1007/978-3-319-67190-1_15
bibtex: '@inproceedings{Mohr_Lettmann_Hüllermeier_2017, title={Planning with Independent
Task Networks}, DOI={10.1007/978-3-319-67190-1_15},
booktitle={Proc. 40th Annual German Conference on Advances in Artificial Intelligence
(KI 2017)}, author={Mohr, Felix and Lettmann, Theodor and Hüllermeier, Eyke},
year={2017}, pages={193–206} }'
chicago: Mohr, Felix, Theodor Lettmann, and Eyke Hüllermeier. “Planning with Independent
Task Networks.” In Proc. 40th Annual German Conference on Advances in Artificial
Intelligence (KI 2017), 193–206, 2017. https://doi.org/10.1007/978-3-319-67190-1_15.
ieee: F. Mohr, T. Lettmann, and E. Hüllermeier, “Planning with Independent Task
Networks,” in Proc. 40th Annual German Conference on Advances in Artificial
Intelligence (KI 2017), 2017, pp. 193–206.
mla: Mohr, Felix, et al. “Planning with Independent Task Networks.” Proc. 40th
Annual German Conference on Advances in Artificial Intelligence (KI 2017),
2017, pp. 193–206, doi:10.1007/978-3-319-67190-1_15.
short: 'F. Mohr, T. Lettmann, E. Hüllermeier, in: Proc. 40th Annual German Conference
on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206.'
date_created: 2019-06-07T15:24:16Z
date_updated: 2022-01-06T06:50:31Z
ddc:
- '000'
department:
- _id: '7'
- _id: '34'
- _id: '355'
doi: 10.1007/978-3-319-67190-1_15
file:
- access_level: open_access
content_type: application/pdf
creator: lettmann
date_created: 2020-02-28T12:50:18Z
date_updated: 2020-02-28T12:50:18Z
file_id: '16157'
file_name: ki17.pdf
file_size: 374421
relation: main_file
file_date_updated: 2020-02-28T12:50:18Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 193-206
publication: Proc. 40th Annual German Conference on Advances in Artificial Intelligence
(KI 2017)
status: public
title: Planning with Independent Task Networks
type: conference
user_id: '315'
year: '2017'
...
---
_id: '10207'
author:
- first_name: M.
full_name: Czech, M.
last_name: Czech
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: M.-C.
full_name: Jakobs, M.-C.
last_name: Jakobs
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: 'Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting rankings of software
verification tools. In: Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics
(SWAN@ESEC/SIGSOFT FSE 2017. ; 2017:23-26.'
apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting
rankings of software verification tools. In Proc. 3rd ACM SIGSOFT Int. I Workshop
on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017 (pp. 23–26).
bibtex: '@inproceedings{Czech_Hüllermeier_Jakobs_Wehrheim_2017, title={Predicting
rankings of software verification tools}, booktitle={Proc. 3rd ACM SIGSOFT Int.
I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017}, author={Czech,
M. and Hüllermeier, Eyke and Jakobs, M.-C. and Wehrheim, Heike}, year={2017},
pages={23–26} }'
chicago: Czech, M., Eyke Hüllermeier, M.-C. Jakobs, and Heike Wehrheim. “Predicting
Rankings of Software Verification Tools.” In Proc. 3rd ACM SIGSOFT Int. I Workshop
on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 23–26, 2017.
ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, “Predicting rankings
of software verification tools,” in Proc. 3rd ACM SIGSOFT Int. I Workshop on
Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26.
mla: Czech, M., et al. “Predicting Rankings of Software Verification Tools.” Proc.
3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017,
2017, pp. 23–26.
short: 'M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proc. 3rd ACM SIGSOFT
Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26.'
date_created: 2019-06-07T15:27:47Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 23-26
publication: Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT
FSE 2017
status: public
title: Predicting rankings of software verification tools
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10208'
author:
- first_name: Ines
full_name: Couso, Ines
last_name: Couso
- first_name: D.
full_name: Dubois, D.
last_name: Dubois
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Couso I, Dubois D, Hüllermeier E. Maximum Likelihood Estimation and Coarse
Data. In: Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017).
; 2017:3-16.'
apa: Couso, I., Dubois, D., & Hüllermeier, E. (2017). Maximum Likelihood Estimation
and Coarse Data. In Proc. 11th Int. Conf. on Scalable Uncertainty Management
(SUM 2017) (pp. 3–16).
bibtex: '@inproceedings{Couso_Dubois_Hüllermeier_2017, title={Maximum Likelihood
Estimation and Coarse Data}, booktitle={Proc. 11th Int. Conf. on Scalable Uncertainty
Management (SUM 2017)}, author={Couso, Ines and Dubois, D. and Hüllermeier, Eyke},
year={2017}, pages={3–16} }'
chicago: Couso, Ines, D. Dubois, and Eyke Hüllermeier. “Maximum Likelihood Estimation
and Coarse Data.” In Proc. 11th Int. Conf. on Scalable Uncertainty Management
(SUM 2017), 3–16, 2017.
ieee: I. Couso, D. Dubois, and E. Hüllermeier, “Maximum Likelihood Estimation and
Coarse Data,” in Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM
2017), 2017, pp. 3–16.
mla: Couso, Ines, et al. “Maximum Likelihood Estimation and Coarse Data.” Proc.
11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 2017, pp. 3–16.
short: 'I. Couso, D. Dubois, E. Hüllermeier, in: Proc. 11th Int. Conf. on Scalable
Uncertainty Management (SUM 2017), 2017, pp. 3–16.'
date_created: 2019-06-07T15:30:48Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 3-16
publication: Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017)
status: public
title: Maximum Likelihood Estimation and Coarse Data
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10209'
author:
- first_name: Mohsen
full_name: Ahmadi Fahandar, Mohsen
last_name: Ahmadi Fahandar
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Ahmadi Fahandar M, Hüllermeier E. Learning to Rank based on Analogical Reasoning.
In: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence. ;
2017.'
apa: Ahmadi Fahandar, M., & Hüllermeier, E. (2017). Learning to Rank based on
Analogical Reasoning. In Proc. AAAI 2017, 32nd AAAI Conference on Artificial
Intelligence.
bibtex: '@inproceedings{Ahmadi Fahandar_Hüllermeier_2017, title={Learning to Rank
based on Analogical Reasoning}, booktitle={Proc. AAAI 2017, 32nd AAAI Conference
on Artificial Intelligence}, author={Ahmadi Fahandar, Mohsen and Hüllermeier,
Eyke}, year={2017} }'
chicago: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based
on Analogical Reasoning.” In Proc. AAAI 2017, 32nd AAAI Conference on Artificial
Intelligence, 2017.
ieee: M. Ahmadi Fahandar and E. Hüllermeier, “Learning to Rank based on Analogical
Reasoning,” in Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence,
2017.
mla: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical
Reasoning.” Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence,
2017.
short: 'M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. AAAI 2017, 32nd AAAI Conference
on Artificial Intelligence, 2017.'
date_created: 2019-06-07T15:33:14Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence
status: public
title: Learning to Rank based on Analogical Reasoning
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10212'
author:
- first_name: F.
full_name: Hoffmann, F.
last_name: Hoffmann
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: R.
full_name: Mikut, R.
last_name: Mikut
citation:
ama: 'Hoffmann F, Hüllermeier E, Mikut R. (Hrsg.) Proceedings 27. Workshop Computational
Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017. In: ; 2017.'
apa: Hoffmann, F., Hüllermeier, E., & Mikut, R. (2017). (Hrsg.) Proceedings
27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe,
Germany 2017.
bibtex: '@inproceedings{Hoffmann_Hüllermeier_Mikut_2017, title={(Hrsg.) Proceedings
27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe,
Germany 2017}, author={Hoffmann, F. and Hüllermeier, Eyke and Mikut, R.}, year={2017}
}'
chicago: Hoffmann, F., Eyke Hüllermeier, and R. Mikut. “(Hrsg.) Proceedings 27.
Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany
2017,” 2017.
ieee: F. Hoffmann, E. Hüllermeier, and R. Mikut, “(Hrsg.) Proceedings 27. Workshop
Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017,”
2017.
mla: Hoffmann, F., et al. (Hrsg.) Proceedings 27. Workshop Computational Intelligence,
KIT Scientific Publishing, Karlsruhe, Germany 2017. 2017.
short: 'F. Hoffmann, E. Hüllermeier, R. Mikut, in: 2017.'
date_created: 2019-06-07T15:46:10Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
status: public
title: (Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific
Publishing, Karlsruhe, Germany 2017
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10213'
author:
- first_name: Vitaly
full_name: Melnikov, Vitaly
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics. In: Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017. ; 2017:1-12.'
apa: 'Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics. In Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017 (pp. 1–12).'
bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure
of Nested Dichotomies: A Comparison of Two Heuristics}, booktitle={Proceedings
27. Workshop Computational Intelligence, Dortmund, Germany 2017}, author={Melnikov,
Vitaly and Hüllermeier, Eyke}, year={2017}, pages={1–12} }'
chicago: 'Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics.” In Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 1–12, 2017.'
ieee: 'V. Melnikov and E. Hüllermeier, “Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics,” in Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.'
mla: 'Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics.” Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.'
short: 'V. Melnikov, E. Hüllermeier, in: Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.'
date_created: 2019-06-07T15:49:36Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 1-12
publication: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany
2017
status: public
title: 'Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics'
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10216'
author:
- first_name: Ammar
full_name: Shaker, Ammar
last_name: Shaker
- first_name: W.
full_name: Heldt, W.
last_name: Heldt
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Shaker A, Heldt W, Hüllermeier E. Learning TSK Fuzzy Rules from Data Streams.
In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge
Discovery in Databases, Skopje, Macedonia. ; 2017.'
apa: Shaker, A., Heldt, W., & Hüllermeier, E. (2017). Learning TSK Fuzzy Rules
from Data Streams. In Proceedings ECML/PKDD, European Conference on Machine
Learning and Knowledge Discovery in Databases, Skopje, Macedonia.
bibtex: '@inproceedings{Shaker_Heldt_Hüllermeier_2017, title={Learning TSK Fuzzy
Rules from Data Streams}, booktitle={Proceedings ECML/PKDD, European Conference
on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia},
author={Shaker, Ammar and Heldt, W. and Hüllermeier, Eyke}, year={2017} }'
chicago: Shaker, Ammar, W. Heldt, and Eyke Hüllermeier. “Learning TSK Fuzzy Rules
from Data Streams.” In Proceedings ECML/PKDD, European Conference on Machine
Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
ieee: A. Shaker, W. Heldt, and E. Hüllermeier, “Learning TSK Fuzzy Rules from Data
Streams,” in Proceedings ECML/PKDD, European Conference on Machine Learning
and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
mla: Shaker, Ammar, et al. “Learning TSK Fuzzy Rules from Data Streams.” Proceedings
ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in
Databases, Skopje, Macedonia, 2017.
short: 'A. Shaker, W. Heldt, E. Hüllermeier, in: Proceedings ECML/PKDD, European
Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia,
2017.'
date_created: 2019-06-07T16:00:10Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge
Discovery in Databases, Skopje, Macedonia
status: public
title: Learning TSK Fuzzy Rules from Data Streams
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10267'
author:
- first_name: M.
full_name: Bräuning, M.
last_name: Bräuning
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: T.
full_name: Keller, T.
last_name: Keller
- first_name: M.
full_name: Glaum, M.
last_name: Glaum
citation:
ama: Bräuning M, Hüllermeier E, Keller T, Glaum M. Lexicographic preferences for
predictive modeling of human decision making. A new machine learning method with
an application in accounting. European Journal of Operational Research.
2017;258(1):295-306.
apa: Bräuning, M., Hüllermeier, E., Keller, T., & Glaum, M. (2017). Lexicographic
preferences for predictive modeling of human decision making. A new machine learning
method with an application in accounting. European Journal of Operational
Research, 258(1), 295–306.
bibtex: '@article{Bräuning_Hüllermeier_Keller_Glaum_2017, title={Lexicographic preferences
for predictive modeling of human decision making. A new machine learning method
with an application in accounting}, volume={258}, number={1}, journal={European
Journal of Operational Research}, author={Bräuning, M. and Hüllermeier, Eyke and
Keller, T. and Glaum, M.}, year={2017}, pages={295–306} }'
chicago: 'Bräuning, M., Eyke Hüllermeier, T. Keller, and M. Glaum. “Lexicographic
Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning
Method with an Application in Accounting.” European Journal of Operational
Research 258, no. 1 (2017): 295–306.'
ieee: M. Bräuning, E. Hüllermeier, T. Keller, and M. Glaum, “Lexicographic preferences
for predictive modeling of human decision making. A new machine learning method
with an application in accounting,” European Journal of Operational Research,
vol. 258, no. 1, pp. 295–306, 2017.
mla: Bräuning, M., et al. “Lexicographic Preferences for Predictive Modeling of
Human Decision Making. A New Machine Learning Method with an Application in Accounting.”
European Journal of Operational Research, vol. 258, no. 1, 2017, pp. 295–306.
short: M. Bräuning, E. Hüllermeier, T. Keller, M. Glaum, European Journal of Operational
Research 258 (2017) 295–306.
date_created: 2019-06-18T15:43:40Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
intvolume: ' 258'
issue: '1'
language:
- iso: eng
page: 295-306
publication: European Journal of Operational Research
status: public
title: Lexicographic preferences for predictive modeling of human decision making.
A new machine learning method with an application in accounting
type: journal_article
user_id: '49109'
volume: 258
year: '2017'
...
---
_id: '10268'
author:
- first_name: M.-C.
full_name: Platenius, M.-C.
last_name: Platenius
- first_name: Ammar
full_name: Shaker, Ammar
last_name: Shaker
- first_name: M.
full_name: Becker, M.
last_name: Becker
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: W.
full_name: Schäfer, W.
last_name: Schäfer
citation:
ama: Platenius M-C, Shaker A, Becker M, Hüllermeier E, Schäfer W. Imprecise Matching
of Requirements Specifications for Software Services Using Fuzzy Logic. IEEE
Transactions on Software Engineering. 2017;43(8):739-759.
apa: Platenius, M.-C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W.
(2017). Imprecise Matching of Requirements Specifications for Software Services
Using Fuzzy Logic. IEEE Transactions on Software Engineering, 43(8),
739–759.
bibtex: '@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2017, title={Imprecise
Matching of Requirements Specifications for Software Services Using Fuzzy Logic},
volume={43}, number={8}, journal={IEEE Transactions on Software Engineering},
author={Platenius, M.-C. and Shaker, Ammar and Becker, M. and Hüllermeier, Eyke
and Schäfer, W.}, year={2017}, pages={739–759} }'
chicago: 'Platenius, M.-C., Ammar Shaker, M. Becker, Eyke Hüllermeier, and W. Schäfer.
“Imprecise Matching of Requirements Specifications for Software Services Using
Fuzzy Logic.” IEEE Transactions on Software Engineering 43, no. 8 (2017):
739–59.'
ieee: M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise
Matching of Requirements Specifications for Software Services Using Fuzzy Logic,”
IEEE Transactions on Software Engineering, vol. 43, no. 8, pp. 739–759,
2017.
mla: Platenius, M. C., et al. “Imprecise Matching of Requirements Specifications
for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering,
vol. 43, no. 8, 2017, pp. 739–59.
short: M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions
on Software Engineering 43 (2017) 739–759.
date_created: 2019-06-18T15:47:33Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
intvolume: ' 43'
issue: '8'
language:
- iso: eng
page: 739-759
publication: IEEE Transactions on Software Engineering
status: public
title: Imprecise Matching of Requirements Specifications for Software Services Using
Fuzzy Logic
type: journal_article
user_id: '49109'
volume: 43
year: '2017'
...
---
_id: '10269'
article_number: 'abs/1712.00646 '
author:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Hüllermeier E. From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based
Systems: A Critical Reflection. The Computing Research Repository (CoRR).
2017.'
apa: 'Hüllermeier, E. (2017). From Knowledge-based to Data-driven Modeling of Fuzzy
Rule-based Systems: A Critical Reflection. The Computing Research Repository
(CoRR).'
bibtex: '@article{Hüllermeier_2017, title={From Knowledge-based to Data-driven Modeling
of Fuzzy Rule-based Systems: A Critical Reflection}, number={abs/1712.00646},
journal={The Computing Research Repository (CoRR)}, author={Hüllermeier, Eyke},
year={2017} }'
chicago: 'Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy
Rule-Based Systems: A Critical Reflection.” The Computing Research Repository
(CoRR), 2017.'
ieee: 'E. Hüllermeier, “From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based
Systems: A Critical Reflection,” The Computing Research Repository (CoRR),
2017.'
mla: 'Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy
Rule-Based Systems: A Critical Reflection.” The Computing Research Repository
(CoRR), abs/1712.00646, 2017.'
short: E. Hüllermeier, The Computing Research Repository (CoRR) (2017).
date_created: 2019-06-18T15:53:28Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: The Computing Research Repository (CoRR)
status: public
title: 'From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems:
A Critical Reflection'
type: journal_article
user_id: '49109'
year: '2017'
...
---
_id: '24154'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Shalabh
full_name: Bhatnagar, Shalabh
last_name: Bhatnagar
citation:
ama: Ramaswamy A, Bhatnagar S. Stochastic recursive inclusion in two timescales
with an application to the lagrangian dual problem. Stochastics. 2016;88(8):1173-1187.
apa: Ramaswamy, A., & Bhatnagar, S. (2016). Stochastic recursive inclusion in
two timescales with an application to the lagrangian dual problem. Stochastics,
88(8), 1173–1187.
bibtex: '@article{Ramaswamy_Bhatnagar_2016, title={Stochastic recursive inclusion
in two timescales with an application to the lagrangian dual problem}, volume={88},
number={8}, journal={Stochastics}, publisher={Taylor \& Francis}, author={Ramaswamy,
Arunselvan and Bhatnagar, Shalabh}, year={2016}, pages={1173–1187} }'
chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion
in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics
88, no. 8 (2016): 1173–87.'
ieee: A. Ramaswamy and S. Bhatnagar, “Stochastic recursive inclusion in two timescales
with an application to the lagrangian dual problem,” Stochastics, vol.
88, no. 8, pp. 1173–1187, 2016.
mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion
in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics,
vol. 88, no. 8, Taylor \& Francis, 2016, pp. 1173–87.
short: A. Ramaswamy, S. Bhatnagar, Stochastics 88 (2016) 1173–1187.
date_created: 2021-09-10T10:21:49Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
extern: '1'
intvolume: ' 88'
issue: '8'
language:
- iso: eng
page: 1173-1187
publication: Stochastics
publisher: Taylor \& Francis
status: public
title: Stochastic recursive inclusion in two timescales with an application to the
lagrangian dual problem
type: journal_article
user_id: '66937'
volume: 88
year: '2016'
...
---
_id: '3318'
author:
- first_name: Vitalik
full_name: Melnikov, Vitalik
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Daniel
full_name: Kaimann, Daniel
id: '18949'
last_name: Kaimann
- first_name: 'Bernd '
full_name: 'Frick, Bernd '
last_name: Frick
- first_name: ' Pritha '
full_name: 'Gupta, Pritha '
last_name: Gupta
citation:
ama: 'Melnikov V, Hüllermeier E, Kaimann D, Frick B, Gupta Pritha . Pairwise versus
Pointwise Ranking: A Case Study. Schedae Informaticae. 2016;25. doi:10.4467/20838476si.16.006.6187'
apa: 'Melnikov, V., Hüllermeier, E., Kaimann, D., Frick, B., & Gupta, Pritha
. (2016). Pairwise versus Pointwise Ranking: A Case Study. Schedae Informaticae,
25. https://doi.org/10.4467/20838476si.16.006.6187'
bibtex: '@article{Melnikov_Hüllermeier_Kaimann_Frick_Gupta_2016, title={Pairwise
versus Pointwise Ranking: A Case Study}, volume={25}, DOI={10.4467/20838476si.16.006.6187},
journal={Schedae Informaticae}, publisher={Uniwersytet Jagiellonski - Wydawnictwo
Uniwersytetu Jagiellonskiego}, author={Melnikov, Vitalik and Hüllermeier, Eyke
and Kaimann, Daniel and Frick, Bernd and Gupta, Pritha }, year={2016} }'
chicago: 'Melnikov, Vitalik, Eyke Hüllermeier, Daniel Kaimann, Bernd Frick, and Pritha Gupta.
“Pairwise versus Pointwise Ranking: A Case Study.” Schedae Informaticae
25 (2016). https://doi.org/10.4467/20838476si.16.006.6187.'
ieee: 'V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, and Pritha Gupta, “Pairwise
versus Pointwise Ranking: A Case Study,” Schedae Informaticae, vol. 25,
2016.'
mla: 'Melnikov, Vitalik, et al. “Pairwise versus Pointwise Ranking: A Case Study.”
Schedae Informaticae, vol. 25, Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu
Jagiellonskiego, 2016, doi:10.4467/20838476si.16.006.6187.'
short: V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, Pritha Gupta, Schedae
Informaticae 25 (2016).
date_created: 2018-06-22T14:49:40Z
date_updated: 2022-01-06T06:59:10Z
ddc:
- '000'
department:
- _id: '355'
- _id: '183'
doi: 10.4467/20838476si.16.006.6187
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T15:54:38Z
date_updated: 2018-11-02T15:54:38Z
file_id: '5317'
file_name: roz-6-Melnikov.pdf
file_size: 1002478
relation: main_file
success: 1
file_date_updated: 2018-11-02T15:54:38Z
has_accepted_license: '1'
intvolume: ' 25'
language:
- iso: eng
project:
- _id: '3'
name: SFB 901 - Project Area B
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '8'
name: SFB 901 - Subproject A4
- _id: '1'
name: SFB 901
- _id: '2'
name: SFB 901 - Project Area A
publication: Schedae Informaticae
publication_identifier:
issn:
- 2083-8476
publication_status: published
publisher: Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego
status: public
title: 'Pairwise versus Pointwise Ranking: A Case Study'
type: journal_article
user_id: '15504'
volume: 25
year: '2016'
...
---
_id: '190'
abstract:
- lang: eng
text: Today, software components are provided by global markets in the form of services.
In order to optimally satisfy service requesters and service providers, adequate
techniques for automatic service matching are needed. However, a requester’s requirements
may be vague and the information available about a provided service may be incomplete.
As a consequence, fuzziness is induced into the matching procedure. The contribution
of this paper is the development of a systematic matching procedure that leverages
concepts and techniques from fuzzy logic and possibility theory based on our formal
distinction between different sources and types of fuzziness in the context of
service matching. In contrast to existing methods, our approach is able to deal
with imprecision and incompleteness in service specifications and to inform users
about the extent of induced fuzziness in order to improve the user’s decision-making.
We demonstrate our approach on the example of specifications for service reputation
based on ratings given by previous users. Our evaluation based on real service
ratings shows the utility and applicability of our approach.
author:
- first_name: Marie Christin
full_name: Platenius, Marie Christin
last_name: Platenius
- first_name: Ammar
full_name: Shaker, Ammar
last_name: Shaker
- first_name: Matthias
full_name: Becker, Matthias
last_name: Becker
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Wilhelm
full_name: Schäfer, Wilhelm
last_name: Schäfer
citation:
ama: Platenius MC, Shaker A, Becker M, Hüllermeier E, Schäfer W. Imprecise Matching
of Requirements Specifications for Software Services using Fuzzy Logic. IEEE
Transactions on Software Engineering (TSE), presented at ICSE 2017. 2016;(8):739-759.
doi:10.1109/TSE.2016.2632115
apa: Platenius, M. C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W.
(2016). Imprecise Matching of Requirements Specifications for Software Services
using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), Presented
at ICSE 2017, (8), 739–759. https://doi.org/10.1109/TSE.2016.2632115
bibtex: '@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2016, title={Imprecise
Matching of Requirements Specifications for Software Services using Fuzzy Logic},
DOI={10.1109/TSE.2016.2632115},
number={8}, journal={IEEE Transactions on Software Engineering (TSE), presented
at ICSE 2017}, publisher={IEEE}, author={Platenius, Marie Christin and Shaker,
Ammar and Becker, Matthias and Hüllermeier, Eyke and Schäfer, Wilhelm}, year={2016},
pages={739–759} }'
chicago: 'Platenius, Marie Christin, Ammar Shaker, Matthias Becker, Eyke Hüllermeier,
and Wilhelm Schäfer. “Imprecise Matching of Requirements Specifications for Software
Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering (TSE),
Presented at ICSE 2017, no. 8 (2016): 739–59. https://doi.org/10.1109/TSE.2016.2632115.'
ieee: M. C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise
Matching of Requirements Specifications for Software Services using Fuzzy Logic,”
IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017,
no. 8, pp. 739–759, 2016.
mla: Platenius, Marie Christin, et al. “Imprecise Matching of Requirements Specifications
for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering
(TSE), Presented at ICSE 2017, no. 8, IEEE, 2016, pp. 739–59, doi:10.1109/TSE.2016.2632115.
short: M.C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions
on Software Engineering (TSE), Presented at ICSE 2017 (2016) 739–759.
date_created: 2017-10-17T12:41:29Z
date_updated: 2022-01-06T06:53:57Z
ddc:
- '040'
department:
- _id: '355'
doi: 10.1109/TSE.2016.2632115
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T12:30:31Z
date_updated: 2018-03-21T12:30:31Z
file_id: '1529'
file_name: 190-07755807.pdf
file_size: 5225413
relation: main_file
success: 1
file_date_updated: 2018-03-21T12:30:31Z
has_accepted_license: '1'
issue: '8'
language:
- iso: eng
page: 739-759
project:
- _id: '1'
name: SFB 901
- _id: '9'
name: SFB 901 - Subprojekt B1
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '11'
name: SFB 901 - Subprojekt B3
- _id: '3'
name: SFB 901 - Project Area B
publication: IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017
publisher: IEEE
status: public
title: Imprecise Matching of Requirements Specifications for Software Services using
Fuzzy Logic
type: journal_article
user_id: '15504'
year: '2016'
...
---
_id: '184'
abstract:
- lang: eng
text: In this paper, we propose a framework for a class of learning problems that
we refer to as “learning to aggregate”. Roughly, learning-to-aggregate problems
are supervised machine learning problems, in which instances are represented in
the form of a composition of a (variable) number on constituents; such compositions
are associated with an evaluation, score, or label, which is the target of the
prediction task, and which can presumably be modeled in the form of a suitable
aggregation of the properties of its constituents. Our learning-to-aggregate framework
establishes a close connection between machine learning and a branch of mathematics
devoted to the systematic study of aggregation functions. We specifically focus
on a class of functions called uninorms, which combine conjunctive and disjunctive
modes of aggregation. Experimental results for a corresponding model are presented
for a review data set, for which the aggregation problem consists of combining
different reviewer opinions about a paper into an overall decision of acceptance
or rejection.
author:
- first_name: Vitaly
full_name: Melnikov, Vitaly
id: '58747'
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Learning to Aggregate Using Uninorms. In: Proceedings
of the Joint European Conference on Machine Learning and Knowledge Discovery in
Databases (ECML/PKDD 2016). LNCS. ; 2016:756-771. doi:10.1007/978-3-319-46227-1_47'
apa: Melnikov, V., & Hüllermeier, E. (2016). Learning to Aggregate Using Uninorms.
In Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016) (pp. 756–771). https://doi.org/10.1007/978-3-319-46227-1_47
bibtex: '@inproceedings{Melnikov_Hüllermeier_2016, series={LNCS}, title={Learning
to Aggregate Using Uninorms}, DOI={10.1007/978-3-319-46227-1_47},
booktitle={Proceedings of the Joint European Conference on Machine Learning and
Knowledge Discovery in Databases (ECML/PKDD 2016)}, author={Melnikov, Vitaly and
Hüllermeier, Eyke}, year={2016}, pages={756–771}, collection={LNCS} }'
chicago: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.”
In Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016), 756–71. LNCS, 2016. https://doi.org/10.1007/978-3-319-46227-1_47.
ieee: V. Melnikov and E. Hüllermeier, “Learning to Aggregate Using Uninorms,” in
Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771.
mla: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.”
Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–71, doi:10.1007/978-3-319-46227-1_47.
short: 'V. Melnikov, E. Hüllermeier, in: Proceedings of the Joint European Conference
on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016,
pp. 756–771.'
date_created: 2017-10-17T12:41:27Z
date_updated: 2022-01-06T06:53:32Z
ddc:
- '040'
department:
- _id: '355'
doi: 10.1007/978-3-319-46227-1_47
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T12:32:44Z
date_updated: 2018-03-21T12:32:44Z
file_id: '1533'
file_name: 184-chp_3A10.1007_2F978-3-319-46227-1_47.pdf
file_size: 472159
relation: main_file
success: 1
file_date_updated: 2018-03-21T12:32:44Z
has_accepted_license: '1'
language:
- iso: eng
page: 756-771
project:
- _id: '1'
name: SFB 901
- _id: '11'
name: SFB 901 - Subprojekt B3
- _id: '3'
name: SFB 901 - Project Area B
publication: Proceedings of the Joint European Conference on Machine Learning and
Knowledge Discovery in Databases (ECML/PKDD 2016)
series_title: LNCS
status: public
title: Learning to Aggregate Using Uninorms
type: conference
user_id: '15504'
year: '2016'
...
---
_id: '10785'
author:
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds.
Encyclopedia of Machine Learning and Data Mining. Springer; 2016.'
apa: Fürnkranz, J., & Hüllermeier, E. (2016). Preference Learning. In C. Sammut
& G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining.
Springer.
bibtex: '@inbook{Fürnkranz_Hüllermeier_2016, title={Preference Learning}, booktitle={Encyclopedia
of Machine Learning and Data Mining}, publisher={Springer}, author={Fürnkranz,
J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors}, year={2016}
}'
chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb. Springer,
2016.
ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia
of Machine Learning and Data Mining, C. Sammut and G. I. Webb, Eds. Springer,
2016.
mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer,
2016.
short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia
of Machine Learning and Data Mining, Springer, 2016.'
date_created: 2019-07-10T16:00:23Z
date_updated: 2022-01-06T06:50:50Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: C.
full_name: Sammut, C.
last_name: Sammut
- first_name: G.I.
full_name: Webb, G.I.
last_name: Webb
language:
- iso: eng
publication: Encyclopedia of Machine Learning and Data Mining
publisher: Springer
status: public
title: Preference Learning
type: encyclopedia_article
user_id: '49109'
year: '2016'
...
---
_id: '15400'
author:
- first_name: C.
full_name: Labreuche, C.
last_name: Labreuche
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: P.
full_name: Vojtas, P.
last_name: Vojtas
- first_name: A.
full_name: Fallah Tehrani, A.
last_name: Fallah Tehrani
citation:
ama: 'Labreuche C, Hüllermeier E, Vojtas P, Fallah Tehrani A. On the identifiability
of models in multi-criteria preference learning. In: Busa-Fekete R, Hüllermeier
E, Mousseau V, Pfannschmidt K, eds. In Proceedings DA2PL 2016 EURO Mini Conference
From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany.
; 2016.'
apa: Labreuche, C., Hüllermeier, E., Vojtas, P., & Fallah Tehrani, A. (2016).
On the identifiability of models in multi-criteria preference learning. In R.
Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), in
Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid
to Preference Learning, Paderborn Germany.
bibtex: '@inproceedings{Labreuche_Hüllermeier_Vojtas_Fallah Tehrani_2016, title={On
the identifiability of models in multi-criteria preference learning}, booktitle={in
Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid
to Preference Learning, Paderborn Germany}, author={Labreuche, C. and Hüllermeier,
Eyke and Vojtas, P. and Fallah Tehrani, A.}, editor={Busa-Fekete, R. and Hüllermeier,
Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }'
chicago: Labreuche, C., Eyke Hüllermeier, P. Vojtas, and A. Fallah Tehrani. “On
the Identifiability of Models in Multi-Criteria Preference Learning.” In In
Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid
to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete, Eyke
Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016.
ieee: C. Labreuche, E. Hüllermeier, P. Vojtas, and A. Fallah Tehrani, “On the identifiability
of models in multi-criteria preference learning,” in in Proceedings DA2PL
2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning,
Paderborn Germany, 2016.
mla: Labreuche, C., et al. “On the Identifiability of Models in Multi-Criteria
Preference Learning.” In Proceedings DA2PL 2016 EURO Mini Conference From Multiple
Criteria Decision Aid to Preference Learning, Paderborn Germany, edited by
R. Busa-Fekete et al., 2016.
short: 'C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete,
E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016
EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning,
Paderborn Germany, 2016.'
date_created: 2019-12-19T16:02:19Z
date_updated: 2022-01-06T06:52:23Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: R.
full_name: Busa-Fekete, R.
last_name: Busa-Fekete
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: V.
full_name: Mousseau, V.
last_name: Mousseau
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
language:
- iso: eng
publication: in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria
Decision Aid to Preference Learning, Paderborn Germany
status: public
title: On the identifiability of models in multi-criteria preference learning
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '15401'
author:
- first_name: D.
full_name: Schäfer, D.
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Preference -based reinforcement learning using dyad
ranking. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. In
Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid
to Preference Learning, Paderborn, Germany. ; 2016.'
apa: Schäfer, D., & Hüllermeier, E. (2016). Preference -based reinforcement
learning using dyad ranking. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, &
K. Pfannschmidt (Eds.), in Proceedings DA2PL`2016 Euro Mini Conference From
Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany.
bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Preference -based reinforcement
learning using dyad ranking}, booktitle={in Proceedings DA2PL`2016 Euro Mini Conference
From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany},
author={Schäfer, D. and Hüllermeier, Eyke}, editor={Busa-Fekete, R. and Hüllermeier,
Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }'
chicago: Schäfer, D., and Eyke Hüllermeier. “Preference -Based Reinforcement Learning
Using Dyad Ranking.” In In Proceedings DA2PL`2016 Euro Mini Conference From
Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany,
edited by R. Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt,
2016.
ieee: D. Schäfer and E. Hüllermeier, “Preference -based reinforcement learning using
dyad ranking,” in in Proceedings DA2PL`2016 Euro Mini Conference From Multiple
Criteria Decision Aid to Preference Learning, Paderborn, Germany, 2016.
mla: Schäfer, D., and Eyke Hüllermeier. “Preference -Based Reinforcement Learning
Using Dyad Ranking.” In Proceedings DA2PL`2016 Euro Mini Conference From Multiple
Criteria Decision Aid to Preference Learning, Paderborn, Germany, edited by
R. Busa-Fekete et al., 2016.
short: 'D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau,
K. Pfannschmidt (Eds.), In Proceedings DA2PL`2016 Euro Mini Conference From Multiple
Criteria Decision Aid to Preference Learning, Paderborn, Germany, 2016.'
date_created: 2019-12-19T16:33:45Z
date_updated: 2022-01-06T06:52:23Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: R.
full_name: Busa-Fekete, R.
last_name: Busa-Fekete
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: V.
full_name: Mousseau, V.
last_name: Mousseau
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
language:
- iso: eng
publication: in Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria
Decision Aid to Preference Learning, Paderborn, Germany
status: public
title: Preference -based reinforcement learning using dyad ranking
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '15402'
author:
- first_name: Ines
full_name: Couso, Ines
last_name: Couso
- first_name: Mohsen
full_name: Ahmadi Fahandar, Mohsen
last_name: Ahmadi Fahandar
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Couso I, Ahmadi Fahandar M, Hüllermeier E. Statistical Inference for Incomplete
Ranking Data: A Comparison of two likelihood-based estimators. In: Busa-Fekete
R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. In Proceedings DA2PL 2016
EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning,
Paderborn Germany. ; 2016.'
apa: 'Couso, I., Ahmadi Fahandar, M., & Hüllermeier, E. (2016). Statistical
Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators.
In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.),
in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision
Aid to Preference Learning, Paderborn Germany.'
bibtex: '@inproceedings{Couso_Ahmadi Fahandar_Hüllermeier_2016, title={Statistical
Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators},
booktitle={in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria
Decision Aid to Preference Learning, Paderborn Germany}, author={Couso, Ines and
Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke}, editor={Busa-Fekete, R. and Hüllermeier,
Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }'
chicago: 'Couso, Ines, Mohsen Ahmadi Fahandar, and Eyke Hüllermeier. “Statistical
Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.”
In In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision
Aid to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete, Eyke
Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016.'
ieee: 'I. Couso, M. Ahmadi Fahandar, and E. Hüllermeier, “Statistical Inference
for Incomplete Ranking Data: A Comparison of two likelihood-based estimators,”
in in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision
Aid to Preference Learning, Paderborn Germany, 2016.'
mla: 'Couso, Ines, et al. “Statistical Inference for Incomplete Ranking Data: A
Comparison of Two Likelihood-Based Estimators.” In Proceedings DA2PL 2016 EURO
Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn
Germany, edited by R. Busa-Fekete et al., 2016.'
short: 'I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier,
V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016 EURO Mini Conference
From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany,
2016.'
date_created: 2019-12-19T16:37:06Z
date_updated: 2022-01-06T06:52:23Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: R.
full_name: Busa-Fekete, R.
last_name: Busa-Fekete
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: V.
full_name: Mousseau, V.
last_name: Mousseau
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
language:
- iso: eng
publication: in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria
Decision Aid to Preference Learning, Paderborn Germany
status: public
title: 'Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based
estimators'
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '15403'
author:
- first_name: S.
full_name: Lu, S.
last_name: Lu
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Lu S, Hüllermeier E. Support vector classification on noisy data using fuzzy
superset losses. In: Hüllermeier E, Hoffmann F, Mikut R, eds. In Proceedings
26th Workshop Computational Intelligence, Dortmund Germany. KIT Scientific
Publishing; 2016:1-8.'
apa: Lu, S., & Hüllermeier, E. (2016). Support vector classification on noisy
data using fuzzy superset losses. In E. Hüllermeier, F. Hoffmann, & R. Mikut
(Eds.), in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany
(pp. 1–8). KIT Scientific Publishing.
bibtex: '@inproceedings{Lu_Hüllermeier_2016, title={Support vector classification
on noisy data using fuzzy superset losses}, booktitle={in Proceedings 26th Workshop
Computational Intelligence, Dortmund Germany}, publisher={KIT Scientific Publishing},
author={Lu, S. and Hüllermeier, Eyke}, editor={Hüllermeier, Eyke and Hoffmann,
F. and Mikut, R.Editors}, year={2016}, pages={1–8} }'
chicago: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data
Using Fuzzy Superset Losses.” In In Proceedings 26th Workshop Computational
Intelligence, Dortmund Germany, edited by Eyke Hüllermeier, F. Hoffmann, and
R. Mikut, 1–8. KIT Scientific Publishing, 2016.
ieee: S. Lu and E. Hüllermeier, “Support vector classification on noisy data using
fuzzy superset losses,” in in Proceedings 26th Workshop Computational Intelligence,
Dortmund Germany, 2016, pp. 1–8.
mla: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data
Using Fuzzy Superset Losses.” In Proceedings 26th Workshop Computational Intelligence,
Dortmund Germany, edited by Eyke Hüllermeier et al., KIT Scientific Publishing,
2016, pp. 1–8.
short: 'S. Lu, E. Hüllermeier, in: E. Hüllermeier, F. Hoffmann, R. Mikut (Eds.),
In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, KIT
Scientific Publishing, 2016, pp. 1–8.'
date_created: 2019-12-19T16:40:33Z
date_updated: 2022-01-06T06:52:23Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: F.
full_name: Hoffmann, F.
last_name: Hoffmann
- first_name: R.
full_name: Mikut, R.
last_name: Mikut
language:
- iso: eng
page: 1-8
publication: in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany
publisher: KIT Scientific Publishing
status: public
title: Support vector classification on noisy data using fuzzy superset losses
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '15404'
author:
- first_name: D.
full_name: Schäfer, D.
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In
Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany. ; 2016.'
apa: Schäfer, D., & Hüllermeier, E. (2016). Plackett-Luce networks for dyad
ranking. In in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany.
bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Plackett-Luce networks
for dyad ranking}, booktitle={in Workshop LWDA “Lernen, Wissen, Daten, Analysen”
Potsdam, Germany}, author={Schäfer, D. and Hüllermeier, Eyke}, year={2016} }'
chicago: Schäfer, D., and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.”
In In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany,
2016.
ieee: D. Schäfer and E. Hüllermeier, “Plackett-Luce networks for dyad ranking,”
in in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany,
2016.
mla: Schäfer, D., and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.”
In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016.
short: 'D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten,
Analysen” Potsdam, Germany, 2016.'
date_created: 2019-12-19T16:43:27Z
date_updated: 2022-01-06T06:52:23Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: in Workshop LWDA "Lernen, Wissen, Daten, Analysen" Potsdam, Germany
status: public
title: Plackett-Luce networks for dyad ranking
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '15111'
author:
- first_name: Karlson
full_name: Pfannschmidt, Karlson
id: '13472'
last_name: Pfannschmidt
orcid: 0000-0001-9407-7903
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: S.
full_name: Held, S.
last_name: Held
- first_name: R.
full_name: Neiger, R.
last_name: Neiger
citation:
ama: 'Pfannschmidt K, Hüllermeier E, Held S, Neiger R. Evaluating tests in medical
diagnosis-Combining machine learning with game-theoretical concepts. In: In
Proceedings IPMU 16th International Conference on Information Processing and Management
of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands.
Springer; 2016:450-461.'
apa: Pfannschmidt, K., Hüllermeier, E., Held, S., & Neiger, R. (2016). Evaluating
tests in medical diagnosis-Combining machine learning with game-theoretical concepts.
In In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands (pp. 450–461). Springer.
bibtex: '@inproceedings{Pfannschmidt_Hüllermeier_Held_Neiger_2016, title={Evaluating
tests in medical diagnosis-Combining machine learning with game-theoretical concepts},
booktitle={In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands}, publisher={Springer}, author={Pfannschmidt, Karlson and Hüllermeier,
Eyke and Held, S. and Neiger, R.}, year={2016}, pages={450–461} }'
chicago: Pfannschmidt, Karlson, Eyke Hüllermeier, S. Held, and R. Neiger. “Evaluating
Tests in Medical Diagnosis-Combining Machine Learning with Game-Theoretical Concepts.”
In In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands, 450–61. Springer, 2016.
ieee: K. Pfannschmidt, E. Hüllermeier, S. Held, and R. Neiger, “Evaluating tests
in medical diagnosis-Combining machine learning with game-theoretical concepts,”
in In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands, 2016, pp. 450–461.
mla: Pfannschmidt, Karlson, et al. “Evaluating Tests in Medical Diagnosis-Combining
Machine Learning with Game-Theoretical Concepts.” In Proceedings IPMU 16th
International Conference on Information Processing and Management of Uncertainty
in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer,
2016, pp. 450–61.
short: 'K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings
IPMU 16th International Conference on Information Processing and Management of
Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer,
2016, pp. 450–461.'
date_created: 2019-11-21T16:42:47Z
date_updated: 2022-01-06T06:52:15Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 450-461
publication: In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The
Netherlands
publisher: Springer
status: public
title: Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical
concepts
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '16041'
author:
- first_name: M.
full_name: Leinweber, M.
last_name: Leinweber
- first_name: T.
full_name: Fober, T.
last_name: Fober
- first_name: M.
full_name: Strickert, M.
last_name: Strickert
- first_name: L.
full_name: Baumgärtner, L.
last_name: Baumgärtner
- first_name: G.
full_name: Klebe, G.
last_name: Klebe
- first_name: B.
full_name: Freisleben, B.
last_name: Freisleben
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Leinweber M, Fober T, Strickert M, et al. CavSimBase: A database for large
scale comparison of protein binding sites. IEEE Transactions on Knowledge and
Data Engineering. 2016;28(6):1423-1434.'
apa: 'Leinweber, M., Fober, T., Strickert, M., Baumgärtner, L., Klebe, G., Freisleben,
B., & Hüllermeier, E. (2016). CavSimBase: A database for large scale comparison
of protein binding sites. IEEE Transactions on Knowledge and Data Engineering,
28(6), 1423–1434.'
bibtex: '@article{Leinweber_Fober_Strickert_Baumgärtner_Klebe_Freisleben_Hüllermeier_2016,
title={CavSimBase: A database for large scale comparison of protein binding sites},
volume={28}, number={6}, journal={IEEE Transactions on Knowledge and Data Engineering},
author={Leinweber, M. and Fober, T. and Strickert, M. and Baumgärtner, L. and
Klebe, G. and Freisleben, B. and Hüllermeier, Eyke}, year={2016}, pages={1423–1434}
}'
chicago: 'Leinweber, M., T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben,
and Eyke Hüllermeier. “CavSimBase: A Database for Large Scale Comparison of Protein
Binding Sites.” IEEE Transactions on Knowledge and Data Engineering 28,
no. 6 (2016): 1423–34.'
ieee: 'M. Leinweber et al., “CavSimBase: A database for large scale comparison
of protein binding sites,” IEEE Transactions on Knowledge and Data Engineering,
vol. 28, no. 6, pp. 1423–1434, 2016.'
mla: 'Leinweber, M., et al. “CavSimBase: A Database for Large Scale Comparison of
Protein Binding Sites.” IEEE Transactions on Knowledge and Data Engineering,
vol. 28, no. 6, 2016, pp. 1423–34.'
short: M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben,
E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016)
1423–1434.
date_created: 2020-02-24T16:04:59Z
date_updated: 2022-01-06T06:52:42Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
intvolume: ' 28'
issue: '6'
language:
- iso: eng
page: 1423-1434
publication: IEEE Transactions on Knowledge and Data Engineering
status: public
title: 'CavSimBase: A database for large scale comparison of protein binding sites'
type: journal_article
user_id: '49109'
volume: 28
year: '2016'
...
---
_id: '141'
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
citation:
ama: Mohr F. Towards Automated Service Composition Under Quality Constraints.
Universität Paderborn; 2016. doi:10.17619/UNIPB/1-171
apa: Mohr, F. (2016). Towards Automated Service Composition Under Quality Constraints.
Universität Paderborn. https://doi.org/10.17619/UNIPB/1-171
bibtex: '@book{Mohr_2016, title={Towards Automated Service Composition Under Quality
Constraints}, DOI={10.17619/UNIPB/1-171},
publisher={Universität Paderborn}, author={Mohr, Felix}, year={2016} }'
chicago: Mohr, Felix. Towards Automated Service Composition Under Quality Constraints.
Universität Paderborn, 2016. https://doi.org/10.17619/UNIPB/1-171.
ieee: F. Mohr, Towards Automated Service Composition Under Quality Constraints.
Universität Paderborn, 2016.
mla: Mohr, Felix. Towards Automated Service Composition Under Quality Constraints.
Universität Paderborn, 2016, doi:10.17619/UNIPB/1-171.
short: F. Mohr, Towards Automated Service Composition Under Quality Constraints,
Universität Paderborn, 2016.
date_created: 2017-10-17T12:41:19Z
date_updated: 2022-01-06T06:51:55Z
department:
- _id: '355'
doi: 10.17619/UNIPB/1-171
project:
- _id: '1'
name: SFB 901
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '3'
name: SFB 901 - Project Area B
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Hans
full_name: Kleine Büning, Hans
last_name: Kleine Büning
title: Towards Automated Service Composition Under Quality Constraints
type: dissertation
user_id: '477'
year: '2016'
...
---
_id: '10214'
author:
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds.
Encyclopedia of Machine Learning and Data Mining. Springer; 2016.'
apa: Fürnkranz, J., & Hüllermeier, E. (2016). Preference Learning. In C. Sammut
& G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining.
Springer.
bibtex: '@inbook{Fürnkranz_Hüllermeier_2016, title={Preference Learning}, booktitle={Encyclopedia
of Machine Learning and Data Mining}, publisher={Springer}, author={Fürnkranz,
J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors}, year={2016}
}'
chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb. Springer,
2016.
ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia
of Machine Learning and Data Mining, C. Sammut and G. I. Webb, Eds. Springer,
2016.
mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer,
2016.
short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia
of Machine Learning and Data Mining, Springer, 2016.'
date_created: 2019-06-07T15:52:19Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: C.
full_name: Sammut, C.
last_name: Sammut
- first_name: G.I.
full_name: Webb, G.I.
last_name: Webb
language:
- iso: eng
publication: Encyclopedia of Machine Learning and Data Mining
publisher: Springer
status: public
title: Preference Learning
type: book_chapter
user_id: '49109'
year: '2016'
...
---
_id: '10221'
citation:
ama: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings 26. Workshop Computational
Intelligence KIT Scientific Publishing, Karlsruhe, Germany.; 2016.
apa: Hoffmann, F., Hüllermeier, E., & Mikut, R. (Eds.). (2016). Proceedings
26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe,
Germany.
bibtex: '@book{Hoffmann_Hüllermeier_Mikut_2016, title={ Proceedings 26. Workshop
Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany}, year={2016}
}'
chicago: Hoffmann, F., Eyke Hüllermeier, and R. Mikut, eds. Proceedings 26.
Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany,
2016.
ieee: F. Hoffmann, E. Hüllermeier, and R. Mikut, Eds., Proceedings 26. Workshop
Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany.
2016.
mla: Hoffmann, F., et al., editors. Proceedings 26. Workshop Computational Intelligence
KIT Scientific Publishing, Karlsruhe, Germany. 2016.
short: F. Hoffmann, E. Hüllermeier, R. Mikut, eds., Proceedings 26. Workshop Computational
Intelligence KIT Scientific Publishing, Karlsruhe, Germany, 2016.
date_created: 2019-06-11T14:40:45Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: F.
full_name: Hoffmann, F.
last_name: Hoffmann
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: R.
full_name: Mikut, R.
last_name: Mikut
language:
- iso: eng
status: public
title: ' Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing,
Karlsruhe, Germany'
type: conference_editor
user_id: '49109'
year: '2016'
...
---
_id: '10222'
author:
- first_name: K.
full_name: Jasinska, K.
last_name: Jasinska
- first_name: K.
full_name: Dembczynski, K.
last_name: Dembczynski
- first_name: Robert
full_name: Busa-Fekete, Robert
last_name: Busa-Fekete
- first_name: Timo
full_name: Klerx, Timo
last_name: Klerx
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Jasinska K, Dembczynski K, Busa-Fekete R, Klerx T, Hüllermeier E. Extreme
F-measure maximization using sparse probability estimates . In: Balcan MF, Weinberger
KQ, eds. Proceedings ICML-2016, 33th International Conference on Machine Learning,
New York, USA. ; 2016.'
apa: Jasinska, K., Dembczynski, K., Busa-Fekete, R., Klerx, T., & Hüllermeier,
E. (2016). Extreme F-measure maximization using sparse probability estimates .
In M. F. Balcan & K. Q. Weinberger (Eds.), Proceedings ICML-2016, 33th
International Conference on Machine Learning, New York, USA.
bibtex: '@inproceedings{Jasinska_Dembczynski_Busa-Fekete_Klerx_Hüllermeier_2016,
title={Extreme F-measure maximization using sparse probability estimates }, booktitle={Proceedings
ICML-2016, 33th International Conference on Machine Learning, New York, USA},
author={Jasinska, K. and Dembczynski, K. and Busa-Fekete, Robert and Klerx, Timo
and Hüllermeier, Eyke}, editor={Balcan, M.F. and Weinberger, K.Q.Editors}, year={2016}
}'
chicago: Jasinska, K., K. Dembczynski, Robert Busa-Fekete, Timo Klerx, and Eyke
Hüllermeier. “Extreme F-Measure Maximization Using Sparse Probability Estimates
.” In Proceedings ICML-2016, 33th International Conference on Machine Learning,
New York, USA, edited by M.F. Balcan and K.Q. Weinberger, 2016.
ieee: K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, and E. Hüllermeier,
“Extreme F-measure maximization using sparse probability estimates ,” in Proceedings
ICML-2016, 33th International Conference on Machine Learning, New York, USA,
2016.
mla: Jasinska, K., et al. “Extreme F-Measure Maximization Using Sparse Probability
Estimates .” Proceedings ICML-2016, 33th International Conference on Machine
Learning, New York, USA, edited by M.F. Balcan and K.Q. Weinberger, 2016.
short: 'K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, E. Hüllermeier, in:
M.F. Balcan, K.Q. Weinberger (Eds.), Proceedings ICML-2016, 33th International
Conference on Machine Learning, New York, USA, 2016.'
date_created: 2019-06-11T14:47:31Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: M.F.
full_name: Balcan, M.F.
last_name: Balcan
- first_name: K.Q.
full_name: Weinberger, K.Q.
last_name: Weinberger
language:
- iso: eng
publication: Proceedings ICML-2016, 33th International Conference on Machine Learning,
New York, USA
status: public
title: 'Extreme F-measure maximization using sparse probability estimates '
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10223'
author:
- first_name: Vitaly
full_name: Melnikov, Vitaly
id: '58747'
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Learning to aggregate using uninorms, in Proceedings
ECML/PKDD-2016. In: European Conference on Machine Learning and Knowledge Discovery
in Databases, Part II, Riva Del Garda, Italy. ; 2016:756-771.'
apa: Melnikov, V., & Hüllermeier, E. (2016). Learning to aggregate using uninorms,
in Proceedings ECML/PKDD-2016. In European Conference on Machine Learning and
Knowledge Discovery in Databases, Part II, Riva del Garda, Italy (pp. 756–771).
bibtex: '@inproceedings{Melnikov_Hüllermeier_2016, title={Learning to aggregate
using uninorms, in Proceedings ECML/PKDD-2016}, booktitle={European Conference
on Machine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda,
Italy}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, year={2016}, pages={756–771}
}'
chicago: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms,
in Proceedings ECML/PKDD-2016.” In European Conference on Machine Learning
and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 756–71,
2016.
ieee: V. Melnikov and E. Hüllermeier, “Learning to aggregate using uninorms, in
Proceedings ECML/PKDD-2016,” in European Conference on Machine Learning and
Knowledge Discovery in Databases, Part II, Riva del Garda, Italy, 2016, pp.
756–771.
mla: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms,
in Proceedings ECML/PKDD-2016.” European Conference on Machine Learning and
Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp.
756–71.
short: 'V. Melnikov, E. Hüllermeier, in: European Conference on Machine Learning
and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp.
756–771.'
date_created: 2019-06-11T14:51:30Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 756-771
publication: European Conference on Machine Learning and Knowledge Discovery in Databases,
Part II, Riva del Garda, Italy
status: public
title: Learning to aggregate using uninorms, in Proceedings ECML/PKDD-2016
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10224'
author:
- first_name: K.
full_name: Dembczynski, K.
last_name: Dembczynski
- first_name: W.
full_name: Kotlowski, W.
last_name: Kotlowski
- first_name: W.
full_name: Waegeman, W.
last_name: Waegeman
- first_name: Robert
full_name: Busa-Fekete, Robert
last_name: Busa-Fekete
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Dembczynski K, Kotlowski W, Waegeman W, Busa-Fekete R, Hüllermeier E. Consistency
of probalistic classifier trees. In: In Proceedings ECML/PKDD European Conference
on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda,
Italy. ; 2016:511-526.'
apa: Dembczynski, K., Kotlowski, W., Waegeman, W., Busa-Fekete, R., & Hüllermeier,
E. (2016). Consistency of probalistic classifier trees. In In Proceedings ECML/PKDD
European Conference on Maschine Learning and Knowledge Discovery in Databases,
Part II, Riva del Garda, Italy (pp. 511–526).
bibtex: '@inproceedings{Dembczynski_Kotlowski_Waegeman_Busa-Fekete_Hüllermeier_2016,
title={Consistency of probalistic classifier trees}, booktitle={In Proceedings
ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in
Databases, Part II, Riva del Garda, Italy}, author={Dembczynski, K. and Kotlowski,
W. and Waegeman, W. and Busa-Fekete, Robert and Hüllermeier, Eyke}, year={2016},
pages={511–526} }'
chicago: Dembczynski, K., W. Kotlowski, W. Waegeman, Robert Busa-Fekete, and Eyke
Hüllermeier. “Consistency of Probalistic Classifier Trees.” In In Proceedings
ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in
Databases, Part II, Riva Del Garda, Italy, 511–26, 2016.
ieee: K. Dembczynski, W. Kotlowski, W. Waegeman, R. Busa-Fekete, and E. Hüllermeier,
“Consistency of probalistic classifier trees,” in In Proceedings ECML/PKDD
European Conference on Maschine Learning and Knowledge Discovery in Databases,
Part II, Riva del Garda, Italy, 2016, pp. 511–526.
mla: Dembczynski, K., et al. “Consistency of Probalistic Classifier Trees.” In
Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery
in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 511–26.
short: 'K. Dembczynski, W. Kotlowski, W. Waegeman, R. Busa-Fekete, E. Hüllermeier,
in: In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge
Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 511–526.'
date_created: 2019-06-11T14:56:02Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 511-526
publication: In Proceedings ECML/PKDD European Conference on Maschine Learning and
Knowledge Discovery in Databases, Part II, Riva del Garda, Italy
status: public
title: Consistency of probalistic classifier trees
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10225'
author:
- first_name: Aulon
full_name: Shabani, Aulon
last_name: Shabani
- first_name: Adil
full_name: Paul, Adil
last_name: Paul
- first_name: R.
full_name: Platon, R.
last_name: Platon
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Shabani A, Paul A, Platon R, Hüllermeier E. Predicting the electricity consumption
of buildings: An improved CBR approach. In: In Proceedings ICCBR, 24th International
Conference on Case-Based Reasoning, Atlanta, GA, USA. ; 2016:356-369.'
apa: 'Shabani, A., Paul, A., Platon, R., & Hüllermeier, E. (2016). Predicting
the electricity consumption of buildings: An improved CBR approach. In In Proceedings
ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA
(pp. 356–369).'
bibtex: '@inproceedings{Shabani_Paul_Platon_Hüllermeier_2016, title={Predicting
the electricity consumption of buildings: An improved CBR approach}, booktitle={In
Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta,
GA, USA}, author={Shabani, Aulon and Paul, Adil and Platon, R. and Hüllermeier,
Eyke}, year={2016}, pages={356–369} }'
chicago: 'Shabani, Aulon, Adil Paul, R. Platon, and Eyke Hüllermeier. “Predicting
the Electricity Consumption of Buildings: An Improved CBR Approach.” In In
Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta,
GA, USA, 356–69, 2016.'
ieee: 'A. Shabani, A. Paul, R. Platon, and E. Hüllermeier, “Predicting the electricity
consumption of buildings: An improved CBR approach,” in In Proceedings ICCBR,
24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016,
pp. 356–369.'
mla: 'Shabani, Aulon, et al. “Predicting the Electricity Consumption of Buildings:
An Improved CBR Approach.” In Proceedings ICCBR, 24th International Conference
on Case-Based Reasoning, Atlanta, GA, USA, 2016, pp. 356–69.'
short: 'A. Shabani, A. Paul, R. Platon, E. Hüllermeier, in: In Proceedings ICCBR,
24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016,
pp. 356–369.'
date_created: 2019-06-11T15:00:49Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 356-369
publication: In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning,
Atlanta, GA, USA
status: public
title: 'Predicting the electricity consumption of buildings: An improved CBR approach'
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10226'
author:
- first_name: Karlson
full_name: Pfannschmidt, Karlson
id: '13472'
last_name: Pfannschmidt
orcid: 0000-0001-9407-7903
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: S.
full_name: Held, S.
last_name: Held
- first_name: R.
full_name: Neiger, R.
last_name: Neiger
citation:
ama: 'Pfannschmidt K, Hüllermeier E, Held S, Neiger R. Evaluating tests in medical
diagnosis-Combining machine learning with game-theoretical concepts. In: In
Proceedings IPMU 16th International Conference on Information Processing and Management
of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands.
Springer; 2016:450-461.'
apa: Pfannschmidt, K., Hüllermeier, E., Held, S., & Neiger, R. (2016). Evaluating
tests in medical diagnosis-Combining machine learning with game-theoretical concepts.
In In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands (pp. 450–461). Springer.
bibtex: '@inproceedings{Pfannschmidt_Hüllermeier_Held_Neiger_2016, title={Evaluating
tests in medical diagnosis-Combining machine learning with game-theoretical concepts},
booktitle={In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands}, publisher={Springer}, author={Pfannschmidt, Karlson and Hüllermeier,
Eyke and Held, S. and Neiger, R.}, year={2016}, pages={450–461} }'
chicago: Pfannschmidt, Karlson, Eyke Hüllermeier, S. Held, and R. Neiger. “Evaluating
Tests in Medical Diagnosis-Combining Machine Learning with Game-Theoretical Concepts.”
In In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands, 450–61. Springer, 2016.
ieee: K. Pfannschmidt, E. Hüllermeier, S. Held, and R. Neiger, “Evaluating tests
in medical diagnosis-Combining machine learning with game-theoretical concepts,”
in In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven,
The Netherlands, 2016, pp. 450–461.
mla: Pfannschmidt, Karlson, et al. “Evaluating Tests in Medical Diagnosis-Combining
Machine Learning with Game-Theoretical Concepts.” In Proceedings IPMU 16th
International Conference on Information Processing and Management of Uncertainty
in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer,
2016, pp. 450–61.
short: 'K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings
IPMU 16th International Conference on Information Processing and Management of
Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer,
2016, pp. 450–461.'
date_created: 2019-06-11T15:11:54Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 450-461
publication: In Proceedings IPMU 16th International Conference on Information Processing
and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The
Netherlands
publisher: Springer
status: public
title: Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical
concepts
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10227'
author:
- first_name: C.
full_name: Labreuche, C.
last_name: Labreuche
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: P.
full_name: Vojtas, P.
last_name: Vojtas
- first_name: A.
full_name: Fallah Tehrani, A.
last_name: Fallah Tehrani
citation:
ama: 'Labreuche C, Hüllermeier E, Vojtas P, Fallah Tehrani A. On the Identifiability
of models in multi-criteria preference learning . In: Busa-Fekete R, Hüllermeier
E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference
from Multiple Criteria Decision Aid to Preference Learning. ; 2016.'
apa: Labreuche, C., Hüllermeier, E., Vojtas, P., & Fallah Tehrani, A. (2016).
On the Identifiability of models in multi-criteria preference learning . In R.
Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), Proceedings
DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference
Learning.
bibtex: '@inproceedings{Labreuche_Hüllermeier_Vojtas_Fallah Tehrani_2016, title={On
the Identifiability of models in multi-criteria preference learning }, booktitle={Proceedings
DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference
Learning}, author={Labreuche, C. and Hüllermeier, Eyke and Vojtas, P. and Fallah
Tehrani, A.}, editor={Busa-Fekete, Robert and Hüllermeier, Eyke and Mousseau,
V. and Pfannschmidt, KarlsonEditors}, year={2016} }'
chicago: Labreuche, C., Eyke Hüllermeier, P. Vojtas, and A. Fallah Tehrani. “On
the Identifiability of Models in Multi-Criteria Preference Learning .” In Proceedings
DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference
Learning, edited by Robert Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and
Karlson Pfannschmidt, 2016.
ieee: C. Labreuche, E. Hüllermeier, P. Vojtas, and A. Fallah Tehrani, “On the Identifiability
of models in multi-criteria preference learning ,” in Proceedings DA2PL ´2016,
Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning,
2016.
mla: Labreuche, C., et al. “On the Identifiability of Models in Multi-Criteria Preference
Learning .” Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria
Decision Aid to Preference Learning, edited by Robert Busa-Fekete et al.,
2016.
short: 'C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete,
E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016,
Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning,
2016.'
date_created: 2019-06-11T15:34:48Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: Robert
full_name: Busa-Fekete, Robert
last_name: Busa-Fekete
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: V.
full_name: Mousseau, V.
last_name: Mousseau
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
language:
- iso: eng
publication: Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria
Decision Aid to Preference Learning
status: public
title: 'On the Identifiability of models in multi-criteria preference learning '
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10228'
author:
- first_name: Dirk
full_name: Schäfer, Dirk
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad
Ranking. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings
DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference
Learning. ; 2016.'
apa: Schäfer, D., & Hüllermeier, E. (2016). Preference-Based Reinforcement Learning
Using Dyad Ranking. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt
(Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria
Decision Aid to Preference Learning.
bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Preference-Based Reinforcement
Learning Using Dyad Ranking}, booktitle={Proceedings DA2PL ´2016, Euro Mini Conference
from Multiple Criteria Decision Aid to Preference Learning}, author={Schäfer,
Dirk and Hüllermeier, Eyke}, editor={Busa-Fekete, Robert and Hüllermeier, Eyke
and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }'
chicago: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” In Proceedings DA2PL ´2016, Euro Mini Conference from
Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete,
Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016.
ieee: D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using
Dyad Ranking,” in Proceedings DA2PL ´2016, Euro Mini Conference from Multiple
Criteria Decision Aid to Preference Learning, 2016.
mla: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” Proceedings DA2PL ´2016, Euro Mini Conference from Multiple
Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete
et al., 2016.
short: 'D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau,
K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple
Criteria Decision Aid to Preference Learning, 2016.'
date_created: 2019-06-11T15:37:51Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: Robert
full_name: Busa-Fekete, Robert
last_name: Busa-Fekete
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: V.
full_name: Mousseau, V.
last_name: Mousseau
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
language:
- iso: eng
publication: Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria
Decision Aid to Preference Learning
status: public
title: Preference-Based Reinforcement Learning Using Dyad Ranking
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10229'
author:
- first_name: Ines
full_name: Couso, Ines
last_name: Couso
- first_name: Mohsen
full_name: Ahmadi Fahandar, Mohsen
last_name: Ahmadi Fahandar
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Couso I, Ahmadi Fahandar M, Hüllermeier E. Statistical Inference for Incomplete
Ranking Data: A Comparison of two likelihood-based estimators. In: Busa-Fekete
R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016,
Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning.
; 2016.'
apa: 'Couso, I., Ahmadi Fahandar, M., & Hüllermeier, E. (2016). Statistical
Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators.
In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.),
Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision
Aid to Preference Learning.'
bibtex: '@inproceedings{Couso_Ahmadi Fahandar_Hüllermeier_2016, title={Statistical
Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators},
booktitle={Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria
Decision Aid to Preference Learning}, author={Couso, Ines and Ahmadi Fahandar,
Mohsen and Hüllermeier, Eyke}, editor={Busa-Fekete, Robert and Hüllermeier, Eyke
and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }'
chicago: 'Couso, Ines, Mohsen Ahmadi Fahandar, and Eyke Hüllermeier. “Statistical
Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.”
In Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision
Aid to Preference Learning, edited by Robert Busa-Fekete, Eyke Hüllermeier,
V. Mousseau, and Karlson Pfannschmidt, 2016.'
ieee: 'I. Couso, M. Ahmadi Fahandar, and E. Hüllermeier, “Statistical Inference
for Incomplete Ranking Data: A Comparison of two likelihood-based estimators,”
in Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision
Aid to Preference Learning, 2016.'
mla: 'Couso, Ines, et al. “Statistical Inference for Incomplete Ranking Data: A
Comparison of Two Likelihood-Based Estimators.” Proceedings DA2PL ´2016, Euro
Mini Conference from Multiple Criteria Decision Aid to Preference Learning,
edited by Robert Busa-Fekete et al., 2016.'
short: 'I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier,
V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference
from Multiple Criteria Decision Aid to Preference Learning, 2016.'
date_created: 2019-06-11T15:41:55Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: Robert
full_name: Busa-Fekete, Robert
last_name: Busa-Fekete
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: V.
full_name: Mousseau, V.
last_name: Mousseau
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
language:
- iso: eng
publication: Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria
Decision Aid to Preference Learning
status: public
title: 'Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based
estimators'
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10230'
author:
- first_name: S.
full_name: Lu, S.
last_name: Lu
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Lu S, Hüllermeier E. Support vector classification on noisy data using fuzzy
supersets losses. In: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings
26. Workshop Computational Intelligence, KIT Scientific Publishing. ; 2016:1-8.'
apa: Lu, S., & Hüllermeier, E. (2016). Support vector classification on noisy
data using fuzzy supersets losses. In F. Hoffmann, E. Hüllermeier, & R. Mikut
(Eds.), Proceedings 26. Workshop Computational Intelligence, KIT Scientific
Publishing (pp. 1–8).
bibtex: '@inproceedings{Lu_Hüllermeier_2016, title={Support vector classification
on noisy data using fuzzy supersets losses}, booktitle={Proceedings 26. Workshop
Computational Intelligence, KIT Scientific Publishing}, author={Lu, S. and Hüllermeier,
Eyke}, editor={Hoffmann, F. and Hüllermeier, Eyke and Mikut, R.Editors}, year={2016},
pages={1–8} }'
chicago: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data
Using Fuzzy Supersets Losses.” In Proceedings 26. Workshop Computational Intelligence,
KIT Scientific Publishing, edited by F. Hoffmann, Eyke Hüllermeier, and R.
Mikut, 1–8, 2016.
ieee: S. Lu and E. Hüllermeier, “Support vector classification on noisy data using
fuzzy supersets losses,” in Proceedings 26. Workshop Computational Intelligence,
KIT Scientific Publishing, 2016, pp. 1–8.
mla: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data
Using Fuzzy Supersets Losses.” Proceedings 26. Workshop Computational Intelligence,
KIT Scientific Publishing, edited by F. Hoffmann et al., 2016, pp. 1–8.
short: 'S. Lu, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.),
Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing,
2016, pp. 1–8.'
date_created: 2019-06-11T15:46:58Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: F.
full_name: Hoffmann, F.
last_name: Hoffmann
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: R.
full_name: Mikut, R.
last_name: Mikut
language:
- iso: eng
page: 1-8
publication: Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing
status: public
title: Support vector classification on noisy data using fuzzy supersets losses
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10231'
author:
- first_name: Dirk
full_name: Schäfer, Dirk
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In
Workshop LWDA “Lernen, Wissen, Daten, Analysen.” ; 2016.'
apa: Schäfer, D., & Hüllermeier, E. (2016). Plackett-Luce networks for dyad
ranking. In In Workshop LWDA “Lernen, Wissen, Daten, Analysen.”
bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Plackett-Luce networks
for dyad ranking}, booktitle={In Workshop LWDA “Lernen, Wissen, Daten, Analysen”},
author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2016} }'
chicago: Schäfer, Dirk, and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.”
In In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016.
ieee: D. Schäfer and E. Hüllermeier, “Plackett-Luce networks for dyad ranking,”
in In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016.
mla: Schäfer, Dirk, and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.”
In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016.
short: 'D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten,
Analysen,” 2016.'
date_created: 2019-06-11T15:49:26Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: In Workshop LWDA "Lernen, Wissen, Daten, Analysen"
status: public
title: Plackett-Luce networks for dyad ranking
type: conference
user_id: '49109'
year: '2016'
...
---
_id: '10263'
citation:
ama: 'Kaminka GA, Fox M, Bouquet P, et al., eds. ECAI 2016, 22nd European Conference
on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial
Intelligence. Vol 285. The Hague, The Netherlands: IOS Press; 2016.'
apa: 'Kaminka, G. A., Fox, M., Bouquet, P., Hüllermeier, E., Dignum, V., Dignum,
F., & van Harmelen, F. (Eds.). (2016). ECAI 2016, 22nd European Conference
on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial
Intelligence (Vol. 285). The Hague, The Netherlands: IOS Press.'
bibtex: '@book{Kaminka_Fox_Bouquet_Hüllermeier_Dignum_Dignum_van Harmelen_2016,
place={The Hague, The Netherlands}, series={Frontiers in Artificial Intelligence
and Applications, The Hague, The Netherlands}, title={ECAI 2016, 22nd European
Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications
of Artificial Intelligence}, volume={285}, publisher={IOS Press}, year={2016},
collection={Frontiers in Artificial Intelligence and Applications, The Hague,
The Netherlands} }'
chicago: 'Kaminka, G.A., M. Fox, P. Bouquet, Eyke Hüllermeier, V. Dignum, F. Dignum,
and F. van Harmelen, eds. ECAI 2016, 22nd European Conference on Artificial
Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence.
Vol. 285. Frontiers in Artificial Intelligence and Applications, The Hague, The
Netherlands. The Hague, The Netherlands: IOS Press, 2016.'
ieee: 'G. A. Kaminka et al., Eds., ECAI 2016, 22nd European Conference
on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial
Intelligence, vol. 285. The Hague, The Netherlands: IOS Press, 2016.'
mla: Kaminka, G. A., et al., editors. ECAI 2016, 22nd European Conference on
Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial
Intelligence. Vol. 285, IOS Press, 2016.
short: G.A. Kaminka, M. Fox, P. Bouquet, E. Hüllermeier, V. Dignum, F. Dignum, F.
van Harmelen, eds., ECAI 2016, 22nd European Conference on Artificial Intelligence,
Including PAIS 2016, Prestigious Applications of Artificial Intelligence, IOS
Press, The Hague, The Netherlands, 2016.
date_created: 2019-06-18T15:07:10Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: G.A.
full_name: Kaminka, G.A.
last_name: Kaminka
- first_name: M.
full_name: Fox, M.
last_name: Fox
- first_name: P.
full_name: Bouquet, P.
last_name: Bouquet
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: V.
full_name: Dignum, V.
last_name: Dignum
- first_name: F.
full_name: Dignum, F.
last_name: Dignum
- first_name: F.
full_name: van Harmelen, F.
last_name: van Harmelen
intvolume: ' 285'
language:
- iso: eng
place: The Hague, The Netherlands
publisher: IOS Press
series_title: Frontiers in Artificial Intelligence and Applications, The Hague, The
Netherlands
status: public
title: ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS
2016, Prestigious Applications of Artificial Intelligence
type: conference_editor
user_id: '49109'
volume: 285
year: '2016'
...
---
_id: '10264'
author:
- first_name: M.
full_name: Leinweber, M.
last_name: Leinweber
- first_name: T.
full_name: Fober, T.
last_name: Fober
- first_name: M.
full_name: Strickert, M.
last_name: Strickert
- first_name: L.
full_name: Baumgärtner, L.
last_name: Baumgärtner
- first_name: G.
full_name: Klebe, G.
last_name: Klebe
- first_name: B.
full_name: Freisleben, B.
last_name: Freisleben
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Leinweber M, Fober T, Strickert M, et al. CavSimBase: A database for large
scale comparison of protein binding sites. IEEE Transactions on Knowledge and
Data Engineering. 2016;28(6):1423-1434.'
apa: 'Leinweber, M., Fober, T., Strickert, M., Baumgärtner, L., Klebe, G., Freisleben,
B., & Hüllermeier, E. (2016). CavSimBase: A database for large scale comparison
of protein binding sites. IEEE Transactions on Knowledge and Data Engineering,
28(6), 1423–1434.'
bibtex: '@article{Leinweber_Fober_Strickert_Baumgärtner_Klebe_Freisleben_Hüllermeier_2016,
title={CavSimBase: A database for large scale comparison of protein binding sites},
volume={28}, number={6}, journal={IEEE Transactions on Knowledge and Data Engineering},
author={Leinweber, M. and Fober, T. and Strickert, M. and Baumgärtner, L. and
Klebe, G. and Freisleben, B. and Hüllermeier, Eyke}, year={2016}, pages={1423–1434}
}'
chicago: 'Leinweber, M., T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben,
and Eyke Hüllermeier. “CavSimBase: A Database for Large Scale Comparison of Protein
Binding Sites.” IEEE Transactions on Knowledge and Data Engineering 28,
no. 6 (2016): 1423–34.'
ieee: 'M. Leinweber et al., “CavSimBase: A database for large scale comparison
of protein binding sites,” IEEE Transactions on Knowledge and Data Engineering,
vol. 28, no. 6, pp. 1423–1434, 2016.'
mla: 'Leinweber, M., et al. “CavSimBase: A Database for Large Scale Comparison of
Protein Binding Sites.” IEEE Transactions on Knowledge and Data Engineering,
vol. 28, no. 6, 2016, pp. 1423–34.'
short: M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben,
E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016)
1423–1434.
date_created: 2019-06-18T15:29:05Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
intvolume: ' 28'
issue: '6'
language:
- iso: eng
page: 1423-1434
publication: IEEE Transactions on Knowledge and Data Engineering
status: public
title: 'CavSimBase: A database for large scale comparison of protein binding sites'
type: journal_article
user_id: '49109'
volume: 28
year: '2016'
...
---
_id: '10266'
author:
- first_name: M.
full_name: Riemenschneider, M.
last_name: Riemenschneider
- first_name: Robin
full_name: Senge, Robin
last_name: Senge
- first_name: U.
full_name: Neumann, U.
last_name: Neumann
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: D.
full_name: Heider, D.
last_name: Heider
citation:
ama: Riemenschneider M, Senge R, Neumann U, Hüllermeier E, Heider D. Exploiting
HIV-1 protease and reverse transcriptase cross-resistance information for improved
drug resistance prediction by means of multi-label classification. BioData
Mining. 2016;9(10).
apa: Riemenschneider, M., Senge, R., Neumann, U., Hüllermeier, E., & Heider,
D. (2016). Exploiting HIV-1 protease and reverse transcriptase cross-resistance
information for improved drug resistance prediction by means of multi-label classification.
BioData Mining, 9(10).
bibtex: '@article{Riemenschneider_Senge_Neumann_Hüllermeier_Heider_2016, title={Exploiting
HIV-1 protease and reverse transcriptase cross-resistance information for improved
drug resistance prediction by means of multi-label classification}, volume={9},
number={10}, journal={BioData Mining}, author={Riemenschneider, M. and Senge,
Robin and Neumann, U. and Hüllermeier, Eyke and Heider, D.}, year={2016} }'
chicago: Riemenschneider, M., Robin Senge, U. Neumann, Eyke Hüllermeier, and D.
Heider. “Exploiting HIV-1 Protease and Reverse Transcriptase Cross-Resistance
Information for Improved Drug Resistance Prediction by Means of Multi-Label Classification.”
BioData Mining 9, no. 10 (2016).
ieee: M. Riemenschneider, R. Senge, U. Neumann, E. Hüllermeier, and D. Heider, “Exploiting
HIV-1 protease and reverse transcriptase cross-resistance information for improved
drug resistance prediction by means of multi-label classification,” BioData
Mining, vol. 9, no. 10, 2016.
mla: Riemenschneider, M., et al. “Exploiting HIV-1 Protease and Reverse Transcriptase
Cross-Resistance Information for Improved Drug Resistance Prediction by Means
of Multi-Label Classification.” BioData Mining, vol. 9, no. 10, 2016.
short: M. Riemenschneider, R. Senge, U. Neumann, E. Hüllermeier, D. Heider, BioData
Mining 9 (2016).
date_created: 2019-06-18T15:37:19Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
intvolume: ' 9'
issue: '10'
language:
- iso: eng
publication: BioData Mining
status: public
title: Exploiting HIV-1 protease and reverse transcriptase cross-resistance information
for improved drug resistance prediction by means of multi-label classification
type: journal_article
user_id: '49109'
volume: 9
year: '2016'
...
---
_id: '280'
abstract:
- lang: eng
text: The Collaborative Research Centre "On-The-Fly Computing" works on foundations
and principles for the vision of the Future Internet. It proposes the paradigm
of On-The-Fly Computing, which tackles emerging worldwide service markets. In
these markets, service providers trade software, platform, and infrastructure
as a service. Service requesters state requirements on services. To satisfy these
requirements, the new role of brokers, who are (human) actors building service
compositions on the fly, is introduced. Brokers have to specify service compositions
formally and comprehensively using a domain-specific language (DSL), and to use
service matching for the discovery of the constituent services available in the
market. The broker's choice of the DSL and matching approaches influences her
success of building compositions as distinctive properties of different service
markets play a significant role. In this paper, we propose a new approach of engineering
a situation-specific DSL by customizing a comprehensive, modular DSL and its matching
for given service market properties. This enables the broker to create market-specific
composition specifications and to perform market-specific service matching. As
a result, the broker builds service compositions satisfying the requester's requirements
more accurately. We evaluated the presented concepts using case studies in service
markets for tourism and university management.
author:
- first_name: Svetlana
full_name: Arifulina, Svetlana
last_name: Arifulina
- first_name: Marie Christin
full_name: Platenius, Marie Christin
last_name: Platenius
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
- first_name: Wilhelm
full_name: Schäfer, Wilhelm
last_name: Schäfer
citation:
ama: 'Arifulina S, Platenius MC, Mohr F, Engels G, Schäfer W. Market-Specific Service
Compositions: Specification and Matching. In: Proceedings of the IEEE 11th
World Congress on Services (SERVICES), Visionary Track: Service Composition for
the Future Internet. ; 2015:333--340. doi:10.1109/SERVICES.2015.58'
apa: 'Arifulina, S., Platenius, M. C., Mohr, F., Engels, G., & Schäfer, W. (2015).
Market-Specific Service Compositions: Specification and Matching. In Proceedings
of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service
Composition for the Future Internet (pp. 333--340). https://doi.org/10.1109/SERVICES.2015.58'
bibtex: '@inproceedings{Arifulina_Platenius_Mohr_Engels_Schäfer_2015, title={Market-Specific
Service Compositions: Specification and Matching}, DOI={10.1109/SERVICES.2015.58},
booktitle={Proceedings of the IEEE 11th World Congress on Services (SERVICES),
Visionary Track: Service Composition for the Future Internet}, author={Arifulina,
Svetlana and Platenius, Marie Christin and Mohr, Felix and Engels, Gregor and
Schäfer, Wilhelm}, year={2015}, pages={333--340} }'
chicago: 'Arifulina, Svetlana, Marie Christin Platenius, Felix Mohr, Gregor Engels,
and Wilhelm Schäfer. “Market-Specific Service Compositions: Specification and
Matching.” In Proceedings of the IEEE 11th World Congress on Services (SERVICES),
Visionary Track: Service Composition for the Future Internet, 333--340, 2015.
https://doi.org/10.1109/SERVICES.2015.58.'
ieee: 'S. Arifulina, M. C. Platenius, F. Mohr, G. Engels, and W. Schäfer, “Market-Specific
Service Compositions: Specification and Matching,” in Proceedings of the IEEE
11th World Congress on Services (SERVICES), Visionary Track: Service Composition
for the Future Internet, 2015, pp. 333--340.'
mla: 'Arifulina, Svetlana, et al. “Market-Specific Service Compositions: Specification
and Matching.” Proceedings of the IEEE 11th World Congress on Services (SERVICES),
Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340,
doi:10.1109/SERVICES.2015.58.'
short: 'S. Arifulina, M.C. Platenius, F. Mohr, G. Engels, W. Schäfer, in: Proceedings
of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service
Composition for the Future Internet, 2015, pp. 333--340.'
date_created: 2017-10-17T12:41:46Z
date_updated: 2022-01-06T06:57:49Z
ddc:
- '040'
department:
- _id: '66'
- _id: '76'
- _id: '355'
doi: 10.1109/SERVICES.2015.58
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T09:26:04Z
date_updated: 2018-03-21T09:26:04Z
file_id: '1470'
file_name: 280-07196546.pdf
file_size: 234260
relation: main_file
success: 1
file_date_updated: 2018-03-21T09:26:04Z
has_accepted_license: '1'
language:
- iso: eng
page: 333--340
project:
- _id: '1'
name: SFB 901
- _id: '9'
name: SFB 901 - Subprojekt B1
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '3'
name: SFB 901 - Project Area B
publication: 'Proceedings of the IEEE 11th World Congress on Services (SERVICES),
Visionary Track: Service Composition for the Future Internet'
status: public
title: 'Market-Specific Service Compositions: Specification and Matching'
type: conference
user_id: '477'
year: '2015'
...
---
_id: '323'
abstract:
- lang: eng
text: On-the-fly composition of service-based software solutions is still a challenging
task. Even more challenges emerge when facing automatic service composition in
markets of composed services for end users. In this paper, we focus on the functional
discrepancy between “what a user wants” specified in terms of a request and “what
a user gets” when executing a composed service. To meet the challenge of functional
discrepancy, we propose the combination of existing symbolic composition approaches
with machine learning techniques. We developed a learning recommendation system
that expands the capabilities of existing composition algorithms to facilitate
adaptivity and consequently reduces functional discrepancy. As a representative
of symbolic techniques, an Artificial Intelligence planning based approach produces
solutions that are correct with respect to formal specifications. Our learning
recommendation system supports the symbolic approach in decision-making. Reinforcement
Learning techniques enable the recommendation system to adjust its recommendation
strategy over time based on user ratings. We implemented the proposed functionality
in terms of a prototypical composition framework. Preliminary results from experiments
conducted in the image processing domain illustrate the benefit of combining both
complementary techniques.
author:
- first_name: Alexander
full_name: Jungmann, Alexander
last_name: Jungmann
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
citation:
ama: Jungmann A, Mohr F. An approach towards adaptive service composition in markets
of composed services. Journal of Internet Services and Applications. 2015;(1):1-18.
doi:10.1186/s13174-015-0022-8
apa: Jungmann, A., & Mohr, F. (2015). An approach towards adaptive service composition
in markets of composed services. Journal of Internet Services and Applications,
(1), 1–18. https://doi.org/10.1186/s13174-015-0022-8
bibtex: '@article{Jungmann_Mohr_2015, title={An approach towards adaptive service
composition in markets of composed services}, DOI={10.1186/s13174-015-0022-8},
number={1}, journal={Journal of Internet Services and Applications}, publisher={Springer},
author={Jungmann, Alexander and Mohr, Felix}, year={2015}, pages={1–18} }'
chicago: 'Jungmann, Alexander, and Felix Mohr. “An Approach towards Adaptive Service
Composition in Markets of Composed Services.” Journal of Internet Services
and Applications, no. 1 (2015): 1–18. https://doi.org/10.1186/s13174-015-0022-8.'
ieee: A. Jungmann and F. Mohr, “An approach towards adaptive service composition
in markets of composed services,” Journal of Internet Services and Applications,
no. 1, pp. 1–18, 2015.
mla: Jungmann, Alexander, and Felix Mohr. “An Approach towards Adaptive Service
Composition in Markets of Composed Services.” Journal of Internet Services
and Applications, no. 1, Springer, 2015, pp. 1–18, doi:10.1186/s13174-015-0022-8.
short: A. Jungmann, F. Mohr, Journal of Internet Services and Applications (2015)
1–18.
date_created: 2017-10-17T12:41:55Z
date_updated: 2022-01-06T06:59:06Z
ddc:
- '040'
department:
- _id: '355'
doi: 10.1186/s13174-015-0022-8
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-20T07:39:17Z
date_updated: 2018-03-20T07:39:17Z
file_id: '1429'
file_name: 323-An_approach_towards_adaptive_service_composition_in_markets_of_composed_services.pdf
file_size: 2842281
relation: main_file
success: 1
file_date_updated: 2018-03-20T07:39:17Z
has_accepted_license: '1'
issue: '1'
language:
- iso: eng
page: 1-18
project:
- _id: '1'
name: SFB 901
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '3'
name: SFB 901 - Project Area B
publication: Journal of Internet Services and Applications
publisher: Springer
status: public
title: An approach towards adaptive service composition in markets of composed services
type: journal_article
user_id: '477'
year: '2015'
...
---
_id: '324'
abstract:
- lang: eng
text: Services are self-contained software components that can beused platform independent
and that aim at maximizing software reuse. Abasic concern in service oriented
architectures is to measure the reusabilityof services. One of the most important
qualities is the functionalreusability, which indicates how relevant the task
is that a service solves.Current metrics for functional reusability of software,
however, have verylittle explanatory power and do not accomplish this goal.This
paper presents a new approach to estimate the functional reusabilityof services
based on their relevance. To this end, it denes the degreeto which a service enables
the execution of other services as its contri-bution. Based on the contribution,
relevance of services is dened as anestimation for their functional reusability.
Explanatory power is obtainedby normalizing relevance values with a reference
service. The applicationof the metric to a service test set conrms its supposed
capabilities.
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
citation:
ama: 'Mohr F. A Metric for Functional Reusability of Services. In: Proceedings
of the 14th International Conference on Software Reuse (ICSR). LNCS. ; 2015:298--313.
doi:10.1007/978-3-319-14130-5_21'
apa: Mohr, F. (2015). A Metric for Functional Reusability of Services. In Proceedings
of the 14th International Conference on Software Reuse (ICSR) (pp. 298--313).
https://doi.org/10.1007/978-3-319-14130-5_21
bibtex: '@inproceedings{Mohr_2015, series={LNCS}, title={A Metric for Functional
Reusability of Services}, DOI={10.1007/978-3-319-14130-5_21},
booktitle={Proceedings of the 14th International Conference on Software Reuse
(ICSR)}, author={Mohr, Felix}, year={2015}, pages={298--313}, collection={LNCS}
}'
chicago: Mohr, Felix. “A Metric for Functional Reusability of Services.” In Proceedings
of the 14th International Conference on Software Reuse (ICSR), 298--313. LNCS,
2015. https://doi.org/10.1007/978-3-319-14130-5_21.
ieee: F. Mohr, “A Metric for Functional Reusability of Services,” in Proceedings
of the 14th International Conference on Software Reuse (ICSR), 2015, pp. 298--313.
mla: Mohr, Felix. “A Metric for Functional Reusability of Services.” Proceedings
of the 14th International Conference on Software Reuse (ICSR), 2015, pp. 298--313,
doi:10.1007/978-3-319-14130-5_21.
short: 'F. Mohr, in: Proceedings of the 14th International Conference on Software
Reuse (ICSR), 2015, pp. 298--313.'
date_created: 2017-10-17T12:41:55Z
date_updated: 2022-01-06T06:59:07Z
ddc:
- '040'
department:
- _id: '355'
doi: 10.1007/978-3-319-14130-5_21
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-20T07:38:44Z
date_updated: 2018-03-20T07:38:44Z
file_id: '1428'
file_name: 324-ICSR-Mohr-15.pdf
file_size: 569475
relation: main_file
success: 1
file_date_updated: 2018-03-20T07:38:44Z
has_accepted_license: '1'
language:
- iso: eng
page: 298--313
project:
- _id: '1'
name: SFB 901
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '3'
name: SFB 901 - Project Area B
publication: Proceedings of the 14th International Conference on Software Reuse (ICSR)
series_title: LNCS
status: public
title: A Metric for Functional Reusability of Services
type: conference
user_id: '477'
year: '2015'
...
---
_id: '319'
abstract:
- lang: eng
text: Services are self-contained and platform independent software components that
aim at maximizing software reuse. The automated composition of services to a target
software artifact has been tackled with many AI techniques, but existing approaches
make unreasonably strong assumptions such as a predefined data flow, are limited
to tiny problem sizes, ignore non-functional properties, or assume offline service
repositories. This paper presents an algorithm that automatically composes services
without making such assumptions. We employ a backward search algorithm that starts
from an empty composition and prepends service calls to already discovered candidates
until a solution is found. Available services are determined during the search
process. We implemented our algorithm, performed an experimental evaluation, and
compared it to other approaches.
author:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Alexander
full_name: Jungmann, Alexander
last_name: Jungmann
- first_name: Hans
full_name: Kleine Büning, Hans
last_name: Kleine Büning
citation:
ama: 'Mohr F, Jungmann A, Kleine Büning H. Automated Online Service Composition.
In: Proceedings of the 12th IEEE International Conference on Services Computing
(SCC). ; 2015:57--64. doi:10.1109/SCC.2015.18'
apa: Mohr, F., Jungmann, A., & Kleine Büning, H. (2015). Automated Online Service
Composition. In Proceedings of the 12th IEEE International Conference on Services
Computing (SCC) (pp. 57--64). https://doi.org/10.1109/SCC.2015.18
bibtex: '@inproceedings{Mohr_Jungmann_Kleine Büning_2015, title={Automated Online
Service Composition}, DOI={10.1109/SCC.2015.18},
booktitle={Proceedings of the 12th IEEE International Conference on Services Computing
(SCC)}, author={Mohr, Felix and Jungmann, Alexander and Kleine Büning, Hans},
year={2015}, pages={57--64} }'
chicago: Mohr, Felix, Alexander Jungmann, and Hans Kleine Büning. “Automated Online
Service Composition.” In Proceedings of the 12th IEEE International Conference
on Services Computing (SCC), 57--64, 2015. https://doi.org/10.1109/SCC.2015.18.
ieee: F. Mohr, A. Jungmann, and H. Kleine Büning, “Automated Online Service Composition,”
in Proceedings of the 12th IEEE International Conference on Services Computing
(SCC), 2015, pp. 57--64.
mla: Mohr, Felix, et al. “Automated Online Service Composition.” Proceedings
of the 12th IEEE International Conference on Services Computing (SCC), 2015,
pp. 57--64, doi:10.1109/SCC.2015.18.
short: 'F. Mohr, A. Jungmann, H. Kleine Büning, in: Proceedings of the 12th IEEE
International Conference on Services Computing (SCC), 2015, pp. 57--64.'
date_created: 2017-10-17T12:41:54Z
date_updated: 2022-01-06T06:59:04Z
ddc:
- '040'
department:
- _id: '355'
doi: 10.1109/SCC.2015.18
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-20T07:42:03Z
date_updated: 2018-03-20T07:42:03Z
file_id: '1434'
file_name: 319-07207336.pdf
file_size: 345742
relation: main_file
success: 1
file_date_updated: 2018-03-20T07:42:03Z
has_accepted_license: '1'
language:
- iso: eng
page: 57--64
project:
- _id: '1'
name: SFB 901
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '3'
name: SFB 901 - Project Area B
publication: Proceedings of the 12th IEEE International Conference on Services Computing
(SCC)
status: public
title: Automated Online Service Composition
type: conference
user_id: '477'
year: '2015'
...
---
_id: '4792'
author:
- first_name: Robin
full_name: Senge, Robin
last_name: Senge
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Senge R, Hüllermeier E. Fast Fuzzy Pattern Tree Learning for Classification.
IEEE Transactions on Fuzzy Systems. 2015;23(6):2024-2033. doi:10.1109/tfuzz.2015.2396078
apa: Senge, R., & Hüllermeier, E. (2015). Fast Fuzzy Pattern Tree Learning for
Classification. IEEE Transactions on Fuzzy Systems, 23(6), 2024–2033.
https://doi.org/10.1109/tfuzz.2015.2396078
bibtex: '@article{Senge_Hüllermeier_2015, title={Fast Fuzzy Pattern Tree Learning
for Classification}, volume={23}, DOI={10.1109/tfuzz.2015.2396078},
number={6}, journal={IEEE Transactions on Fuzzy Systems}, publisher={Institute
of Electrical and Electronics Engineers (IEEE)}, author={Senge, Robin and Hüllermeier,
Eyke}, year={2015}, pages={2024–2033} }'
chicago: 'Senge, Robin, and Eyke Hüllermeier. “Fast Fuzzy Pattern Tree Learning
for Classification.” IEEE Transactions on Fuzzy Systems 23, no. 6 (2015):
2024–33. https://doi.org/10.1109/tfuzz.2015.2396078.'
ieee: R. Senge and E. Hüllermeier, “Fast Fuzzy Pattern Tree Learning for Classification,”
IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, pp. 2024–2033, 2015.
mla: Senge, Robin, and Eyke Hüllermeier. “Fast Fuzzy Pattern Tree Learning for Classification.”
IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, Institute of Electrical
and Electronics Engineers (IEEE), 2015, pp. 2024–33, doi:10.1109/tfuzz.2015.2396078.
short: R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.
date_created: 2018-10-22T06:53:37Z
date_updated: 2022-01-06T07:01:22Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.1109/tfuzz.2015.2396078
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T15:53:23Z
date_updated: 2018-11-02T15:53:23Z
file_id: '5316'
file_name: 07018950.pdf
file_size: 732827
relation: main_file
success: 1
file_date_updated: 2018-11-02T15:53:23Z
has_accepted_license: '1'
intvolume: ' 23'
issue: '6'
language:
- iso: eng
page: 2024-2033
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '11'
name: SFB 901 - Subproject B3
publication: IEEE Transactions on Fuzzy Systems
publication_identifier:
issn:
- 1063-6706
- 1941-0034
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
status: public
title: Fast Fuzzy Pattern Tree Learning for Classification
type: journal_article
user_id: '49109'
volume: 23
year: '2015'
...
---
_id: '15406'
author:
- first_name: D.
full_name: Schäfer, D.
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Preference-based meta-learning using dyad ranking:
Recommending algorithms in cold-start situations. In: In Proceedings of the
2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located
ECML/PKDD, Porto, Portugal. ; 2015:110-111.'
apa: 'Schäfer, D., & Hüllermeier, E. (2015). Preference-based meta-learning
using dyad ranking: Recommending algorithms in cold-start situations. In in
Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm
Selection co-located ECML/PKDD, Porto, Portugal (pp. 110–111).'
bibtex: '@inproceedings{Schäfer_Hüllermeier_2015, title={Preference-based meta-learning
using dyad ranking: Recommending algorithms in cold-start situations}, booktitle={in
Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm
Selection co-located ECML/PKDD, Porto, Portugal}, author={Schäfer, D. and Hüllermeier,
Eyke}, year={2015}, pages={110–111} }'
chicago: 'Schäfer, D., and Eyke Hüllermeier. “Preference-Based Meta-Learning Using
Dyad Ranking: Recommending Algorithms in Cold-Start Situations.” In In Proceedings
of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located
ECML/PKDD, Porto, Portugal, 110–11, 2015.'
ieee: 'D. Schäfer and E. Hüllermeier, “Preference-based meta-learning using dyad
ranking: Recommending algorithms in cold-start situations,” in in Proceedings
of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located
ECML/PKDD, Porto, Portugal, 2015, pp. 110–111.'
mla: 'Schäfer, D., and Eyke Hüllermeier. “Preference-Based Meta-Learning Using Dyad
Ranking: Recommending Algorithms in Cold-Start Situations.” In Proceedings
of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located
ECML/PKDD, Porto, Portugal, 2015, pp. 110–11.'
short: 'D. Schäfer, E. Hüllermeier, in: In Proceedings of the 2015 International
Workshop on Meta-Learning and Algorithm Selection Co-Located ECML/PKDD, Porto,
Portugal, 2015, pp. 110–111.'
date_created: 2019-12-19T16:52:09Z
date_updated: 2022-01-06T06:52:23Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 110-111
publication: in Proceedings of the 2015 international Workshop on Meta-Learning and
Algorithm Selection co-located ECML/PKDD, Porto, Portugal
status: public
title: 'Preference-based meta-learning using dyad ranking: Recommending algorithms
in cold-start situations'
type: conference
user_id: '49109'
year: '2015'
...
---
_id: '15749'
author:
- first_name: Adil
full_name: Paul, Adil
last_name: Paul
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Paul A, Hüllermeier E. A cbr approach to the angry birds game. In: In Workshop
Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning,
Frankfurt, Germany. ; 2015:68-77.'
apa: Paul, A., & Hüllermeier, E. (2015). A cbr approach to the angry birds game.
In In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based
Reasoning, Frankfurt, Germany (pp. 68–77).
bibtex: '@inproceedings{Paul_Hüllermeier_2015, title={A cbr approach to the angry
birds game}, booktitle={In Workshop Proceedings from ICCBR, 23rd International
Conference on Case-Based Reasoning, Frankfurt, Germany}, author={Paul, Adil and
Hüllermeier, Eyke}, year={2015}, pages={68–77} }'
chicago: Paul, Adil, and Eyke Hüllermeier. “A Cbr Approach to the Angry Birds Game.”
In In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based
Reasoning, Frankfurt, Germany, 68–77, 2015.
ieee: A. Paul and E. Hüllermeier, “A cbr approach to the angry birds game,” in In
Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning,
Frankfurt, Germany, 2015, pp. 68–77.
mla: Paul, Adil, and Eyke Hüllermeier. “A Cbr Approach to the Angry Birds Game.”
In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based
Reasoning, Frankfurt, Germany, 2015, pp. 68–77.
short: 'A. Paul, E. Hüllermeier, in: In Workshop Proceedings from ICCBR, 23rd International
Conference on Case-Based Reasoning, Frankfurt, Germany, 2015, pp. 68–77.'
date_created: 2020-02-03T14:07:45Z
date_updated: 2022-01-06T06:52:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 68-77
publication: In Workshop Proceedings from ICCBR, 23rd International Conference on
Case-Based Reasoning, Frankfurt, Germany
status: public
title: A cbr approach to the angry birds game
type: conference
user_id: '49109'
year: '2015'
...