---
_id: '15025'
abstract:
- lang: eng
text: In software engineering, the imprecise requirements of a user are transformed
to a formal requirements specification during the requirements elicitation process.
This process is usually guided by requirements engineers interviewing the user.
We want to partially automate this first step of the software engineering process
in order to enable users to specify a desired software system on their own. With
our approach, users are only asked to provide exemplary behavioral descriptions.
The problem of synthesizing a requirements specification from examples can partially
be reduced to the problem of grammatical inference, to which we apply an active
coevolutionary learning approach. However, this approach would usually require
many feedback queries to be sent to the user. In this work, we extend and generalize
our active learning approach to receive knowledge from multiple oracles, also
known as proactive learning. The ‘user oracle’ represents input received from
the user and the ‘knowledge oracle’ represents available, formalized domain knowledge.
We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q)
algorithm. We compare FAKT/Q to the active learning approach and provide an extensive
benchmark evaluation. As result we find that the number of required user queries
is reduced and the inference process is sped up significantly. Finally, with so-called
On-The-Fly Markets, we present a motivation and an application of our approach
where such knowledge is available.
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: Lorijn
full_name: van Rooijen, Lorijn
id: '58843'
last_name: van Rooijen
- first_name: Heiko
full_name: Hamann, Heiko
last_name: Hamann
citation:
ama: Wever MD, van Rooijen L, Hamann H. Multi-Oracle Coevolutionary Learning of
Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary
Computation. 2020;28(2):165–193. doi:10.1162/evco_a_00266
apa: Wever, M. D., van Rooijen, L., & Hamann, H. (2020). Multi-Oracle Coevolutionary
Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary
Computation, 28(2), 165–193. https://doi.org/10.1162/evco_a_00266
bibtex: '@article{Wever_van Rooijen_Hamann_2020, title={Multi-Oracle Coevolutionary
Learning of Requirements Specifications from Examples in On-The-Fly Markets},
volume={28}, DOI={10.1162/evco_a_00266},
number={2}, journal={Evolutionary Computation}, publisher={MIT Press Journals},
author={Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko}, year={2020},
pages={165–193} }'
chicago: 'Wever, Marcel Dominik, Lorijn van Rooijen, and Heiko Hamann. “Multi-Oracle
Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly
Markets.” Evolutionary Computation 28, no. 2 (2020): 165–193. https://doi.org/10.1162/evco_a_00266.'
ieee: 'M. D. Wever, L. van Rooijen, and H. Hamann, “Multi-Oracle Coevolutionary
Learning of Requirements Specifications from Examples in On-The-Fly Markets,”
Evolutionary Computation, vol. 28, no. 2, pp. 165–193, 2020, doi: 10.1162/evco_a_00266.'
mla: Wever, Marcel Dominik, et al. “Multi-Oracle Coevolutionary Learning of Requirements
Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation,
vol. 28, no. 2, MIT Press Journals, 2020, pp. 165–193, doi:10.1162/evco_a_00266.
short: M.D. Wever, L. van Rooijen, H. Hamann, Evolutionary Computation 28 (2020)
165–193.
date_created: 2019-11-18T14:19:19Z
date_updated: 2022-01-06T06:52:15Z
department:
- _id: '34'
- _id: '355'
- _id: '26'
- _id: '63'
- _id: '238'
doi: 10.1162/evco_a_00266
intvolume: ' 28'
issue: '2'
language:
- iso: eng
page: 165–193
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Evolutionary Computation
publication_status: published
publisher: MIT Press Journals
related_material:
link:
- relation: confirmation
url: https://www.mitpressjournals.org/doi/pdf/10.1162/evco_a_00266
status: public
title: Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples
in On-The-Fly Markets
type: journal_article
user_id: '15415'
volume: 28
year: '2020'
...
---
_id: '17565'
author:
- first_name: Marie-Luis
full_name: Merten, Marie-Luis
last_name: Merten
- first_name: Nina
full_name: Seemann, Nina
last_name: Seemann
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
citation:
ama: Merten M-L, Seemann N, Wever MD. Grammatikwandel digital-kulturwissenschaftlich
erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff. Niederdeutsches
Jahrbuch. 2019;(142):124-146.
apa: Merten, M.-L., Seemann, N., & Wever, M. D. (2019). Grammatikwandel digital-kulturwissenschaftlich
erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff. Niederdeutsches
Jahrbuch, 142, 124–146.
bibtex: '@article{Merten_Seemann_Wever_2019, title={Grammatikwandel digital-kulturwissenschaftlich
erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff},
number={142}, journal={Niederdeutsches Jahrbuch}, author={Merten, Marie-Luis and
Seemann, Nina and Wever, Marcel Dominik}, year={2019}, pages={124–146} }'
chicago: 'Merten, Marie-Luis, Nina Seemann, and Marcel Dominik Wever. “Grammatikwandel
digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher Sprachausbau im
interdisziplinären Zugriff.” Niederdeutsches Jahrbuch, no. 142 (2019):
124–46.'
ieee: M.-L. Merten, N. Seemann, and M. D. Wever, “Grammatikwandel digital-kulturwissenschaftlich
erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff,”
Niederdeutsches Jahrbuch, no. 142, pp. 124–146, 2019.
mla: Merten, Marie-Luis, et al. “Grammatikwandel digital-kulturwissenschaftlich
erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff.”
Niederdeutsches Jahrbuch, no. 142, 2019, pp. 124–46.
short: M.-L. Merten, N. Seemann, M.D. Wever, Niederdeutsches Jahrbuch (2019) 124–146.
date_created: 2020-08-03T13:55:04Z
date_updated: 2022-01-06T06:53:15Z
department:
- _id: '34'
- _id: '355'
- _id: '26'
issue: '142'
language:
- iso: ger
page: 124-146
project:
- _id: '39'
name: InterGramm
publication: Niederdeutsches Jahrbuch
publication_status: published
status: public
title: Grammatikwandel digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher
Sprachausbau im interdisziplinären Zugriff
type: journal_article
user_id: '5786'
year: '2019'
...
---
_id: '8868'
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
- first_name: Alexander
full_name: Hetzer, Alexander
id: '38209'
last_name: Hetzer
citation:
ama: 'Wever MD, Mohr F, Hüllermeier E, Hetzer A. Towards Automated Machine Learning
for Multi-Label Classification. In: ; 2019.'
apa: Wever, M. D., Mohr, F., Hüllermeier, E., & Hetzer, A. (2019). Towards Automated
Machine Learning for Multi-Label Classification. Presented at the European Conference
on Data Analytics (ECDA), Bayreuth, Germany.
bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_Hetzer_2019, title={Towards Automated
Machine Learning for Multi-Label Classification}, author={Wever, Marcel Dominik
and Mohr, Felix and Hüllermeier, Eyke and Hetzer, Alexander}, year={2019} }'
chicago: Wever, Marcel Dominik, Felix Mohr, Eyke Hüllermeier, and Alexander Hetzer.
“Towards Automated Machine Learning for Multi-Label Classification,” 2019.
ieee: M. D. Wever, F. Mohr, E. Hüllermeier, and A. Hetzer, “Towards Automated Machine
Learning for Multi-Label Classification,” presented at the European Conference
on Data Analytics (ECDA), Bayreuth, Germany, 2019.
mla: Wever, Marcel Dominik, et al. Towards Automated Machine Learning for Multi-Label
Classification. 2019.
short: 'M.D. Wever, F. Mohr, E. Hüllermeier, A. Hetzer, in: 2019.'
conference:
end_date: 2019-03-20
location: Bayreuth, Germany
name: European Conference on Data Analytics (ECDA)
start_date: 2019-03-18
date_created: 2019-04-10T07:17:55Z
date_updated: 2022-01-06T07:04:04Z
ddc:
- '000'
department:
- _id: '355'
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2019-04-10T07:17:17Z
date_updated: 2019-04-10T07:17:17Z
file_id: '8870'
file_name: Towards_Automated_Machine_Learning_for_Multi_Label_Classification.pdf
file_size: '74484'
relation: main_file
success: 1
file_date_updated: 2019-04-10T07:17:17Z
has_accepted_license: '1'
language:
- iso: eng
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: Towards Automated Machine Learning for Multi-Label Classification
type: conference_abstract
user_id: '49109'
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: '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: '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: '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: '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: '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: '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: '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: '119'
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
citation:
ama: Wever MD. Active Learning of User Requirement Specifications in Dynamic
Software Service Markets. Universität Paderborn; 2017.
apa: Wever, M. D. (2017). Active Learning of User Requirement Specifications
in Dynamic Software Service Markets. Universität Paderborn.
bibtex: '@book{Wever_2017, title={Active Learning of User Requirement Specifications
in Dynamic Software Service Markets}, publisher={Universität Paderborn}, author={Wever,
Marcel Dominik}, year={2017} }'
chicago: Wever, Marcel Dominik. Active Learning of User Requirement Specifications
in Dynamic Software Service Markets. Universität Paderborn, 2017.
ieee: M. D. Wever, Active Learning of User Requirement Specifications in Dynamic
Software Service Markets. Universität Paderborn, 2017.
mla: Wever, Marcel Dominik. Active Learning of User Requirement Specifications
in Dynamic Software Service Markets. Universität Paderborn, 2017.
short: M.D. Wever, Active Learning of User Requirement Specifications in Dynamic
Software Service Markets, Universität Paderborn, 2017.
date_created: 2017-10-17T12:41:14Z
date_updated: 2022-01-06T06:51:12Z
ddc:
- '000'
file:
- access_level: open_access
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:31:48Z
date_updated: 2020-07-16T11:53:45Z
file_id: '5388'
file_name: MT-export-2017-03-17.pdf
file_size: 4012186
relation: main_file
file_date_updated: 2020-07-16T11:53:45Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '9'
name: SFB 901 - Subprojekt B1
- _id: '3'
name: SFB 901 - Project Area B
publisher: Universität Paderborn
status: public
title: Active Learning of User Requirement Specifications in Dynamic Software Service
Markets
type: mastersthesis
user_id: '33176'
year: '2017'
...
---
_id: '120'
abstract:
- lang: eng
text: 'Within software engineering, requirements engineering starts from imprecise
and vague user requirements descriptions and infers precise, formalized specifications.
Techniques, such as interviewing by requirements engineers, are typically applied
to identify the user’s needs. We want to partially automate even this first step
of requirements elicitation by methods of evolutionary computation. The idea is
to enable users to specify their desired software by listing examples of behavioral
descriptions. Users initially specify two lists of operation sequences, one with
desired behaviors and one with forbidden behaviors. Then, we search for the appropriate
formal software specification in the form of a deterministic finite automaton.
We solve this problem known as grammatical inference with an active coevolutionary
approach following Bongard and Lipson [2]. The coevolutionary process alternates
between two phases: (A) additional training data is actively proposed by an evolutionary
process and the user is interactively asked to label it; (B) appropriate automata
are then evolved to solve this extended grammatical inference problem. Our approach
leverages multi-objective evolution in both phases and outperforms the state-of-the-art
technique [2] for input alphabet sizes of three and more, which are relevant to
our problem domain of requirements specification.'
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: Lorijn
full_name: van Rooijen, Lorijn
id: '58843'
last_name: van Rooijen
- first_name: Heiko
full_name: Hamann, Heiko
last_name: Hamann
citation:
ama: 'Wever MD, van Rooijen L, Hamann H. Active Coevolutionary Learning of Requirements
Specifications from Examples. In: Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO). ; 2017:1327--1334. doi:10.1145/3071178.3071258'
apa: Wever, M. D., van Rooijen, L., & Hamann, H. (2017). Active Coevolutionary
Learning of Requirements Specifications from Examples. In Proceedings of the
Genetic and Evolutionary Computation Conference (GECCO) (pp. 1327--1334).
https://doi.org/10.1145/3071178.3071258
bibtex: '@inproceedings{Wever_van Rooijen_Hamann_2017, title={Active Coevolutionary
Learning of Requirements Specifications from Examples}, DOI={10.1145/3071178.3071258},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference
(GECCO)}, author={Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko},
year={2017}, pages={1327--1334} }'
chicago: Wever, Marcel Dominik, Lorijn van Rooijen, and Heiko Hamann. “Active Coevolutionary
Learning of Requirements Specifications from Examples.” In Proceedings of the
Genetic and Evolutionary Computation Conference (GECCO), 1327--1334, 2017.
https://doi.org/10.1145/3071178.3071258.
ieee: M. D. Wever, L. van Rooijen, and H. Hamann, “Active Coevolutionary Learning
of Requirements Specifications from Examples,” in Proceedings of the Genetic
and Evolutionary Computation Conference (GECCO), 2017, pp. 1327--1334.
mla: Wever, Marcel Dominik, et al. “Active Coevolutionary Learning of Requirements
Specifications from Examples.” Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO), 2017, pp. 1327--1334, doi:10.1145/3071178.3071258.
short: 'M.D. Wever, L. van Rooijen, H. Hamann, in: Proceedings of the Genetic and
Evolutionary Computation Conference (GECCO), 2017, pp. 1327--1334.'
date_created: 2017-10-17T12:41:15Z
date_updated: 2022-01-06T06:51:15Z
ddc:
- '000'
department:
- _id: '66'
doi: 10.1145/3071178.3071258
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T15:00:35Z
date_updated: 2018-11-02T15:00:35Z
file_id: '5290'
file_name: p1327-wever.pdf
file_size: 1092021
relation: main_file
success: 1
file_date_updated: 2018-11-02T15:00:35Z
has_accepted_license: '1'
language:
- iso: eng
page: 1327--1334
project:
- _id: '1'
name: SFB 901
- _id: '9'
name: SFB 901 - Subproject B1
- _id: '3'
name: SFB 901 - Project Area B
publication: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)
status: public
title: Active Coevolutionary Learning of Requirements Specifications from Examples
type: conference
user_id: '477'
year: '2017'
...