---
_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: '1373'
author:
- first_name: Matthias
full_name: Herlich, Matthias
last_name: Herlich
- first_name: Nico
full_name: Bredenbals, Nico
last_name: Bredenbals
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: 'Herlich M, Bredenbals N, Karl H. Delayed (de-)activation in servers with a
sleep mode. Sustainable Computing: Informatics and Systems. 2016;10:48-55.
doi:10.1016/j.suscom.2016.04.002'
apa: 'Herlich, M., Bredenbals, N., & Karl, H. (2016). Delayed (de-)activation
in servers with a sleep mode. Sustainable Computing: Informatics and Systems,
10, 48–55. https://doi.org/10.1016/j.suscom.2016.04.002'
bibtex: '@article{Herlich_Bredenbals_Karl_2016, title={Delayed (de-)activation in
servers with a sleep mode}, volume={10}, DOI={10.1016/j.suscom.2016.04.002},
journal={Sustainable Computing: Informatics and Systems}, publisher={Elsevier
BV}, author={Herlich, Matthias and Bredenbals, Nico and Karl, Holger}, year={2016},
pages={48–55} }'
chicago: 'Herlich, Matthias, Nico Bredenbals, and Holger Karl. “Delayed (de-)Activation
in Servers with a Sleep Mode.” Sustainable Computing: Informatics and Systems
10 (2016): 48–55. https://doi.org/10.1016/j.suscom.2016.04.002.'
ieee: 'M. Herlich, N. Bredenbals, and H. Karl, “Delayed (de-)activation in servers
with a sleep mode,” Sustainable Computing: Informatics and Systems, vol.
10, pp. 48–55, 2016.'
mla: 'Herlich, Matthias, et al. “Delayed (de-)Activation in Servers with a Sleep
Mode.” Sustainable Computing: Informatics and Systems, vol. 10, Elsevier
BV, 2016, pp. 48–55, doi:10.1016/j.suscom.2016.04.002.'
short: 'M. Herlich, N. Bredenbals, H. Karl, Sustainable Computing: Informatics and
Systems 10 (2016) 48–55.'
date_created: 2018-03-19T13:29:17Z
date_updated: 2022-01-06T06:51:43Z
department:
- _id: '75'
doi: 10.1016/j.suscom.2016.04.002
intvolume: ' 10'
page: 48-55
publication: 'Sustainable Computing: Informatics and Systems'
publication_identifier:
issn:
- 2210-5379
publication_status: published
publisher: Elsevier BV
status: public
title: Delayed (de-)activation in servers with a sleep mode
type: journal_article
user_id: '15572'
volume: 10
year: '2016'
...
---
_id: '137'
abstract:
- lang: eng
text: Wikidata is the new, large-scale knowledge base of the Wikimedia Foundation.
Its knowledge is increasingly used within Wikipedia itself and various other kinds
of information systems, imposing high demands on its integrity.Wikidata can be
edited by anyone and, unfortunately, it frequently gets vandalized, exposing all
information systems using it to the risk of spreading vandalized and falsified
information. In this paper, we present a new machine learning-based approach to
detect vandalism in Wikidata.We propose a set of 47 features that exploit both
content and context information, and we report on 4 classifiers of increasing
effectiveness tailored to this learning task. Our approach is evaluated on the
recently published Wikidata Vandalism Corpus WDVC-2015 and it achieves an area
under curve value of the receiver operating characteristic, ROC-AUC, of 0.991.
It significantly outperforms the state of the art represented by the rule-based
Wikidata Abuse Filter (0.865 ROC-AUC) and a prototypical vandalism detector recently
introduced by Wikimedia within the Objective Revision Evaluation Service (0.859
ROC-AUC).
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Matthias
full_name: Potthast, Matthias
last_name: Potthast
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Heindorf S, Potthast M, Stein B, Engels G. Vandalism Detection in Wikidata.
In: Proceedings of the 25th International Conference on Information and Knowledge
Management (CIKM 2016). ; 2016:327--336. doi:10.1145/2983323.2983740'
apa: Heindorf, S., Potthast, M., Stein, B., & Engels, G. (2016). Vandalism Detection
in Wikidata. Proceedings of the 25th International Conference on Information
and Knowledge Management (CIKM 2016), 327--336. https://doi.org/10.1145/2983323.2983740
bibtex: '@inproceedings{Heindorf_Potthast_Stein_Engels_2016, title={Vandalism Detection
in Wikidata}, DOI={10.1145/2983323.2983740},
booktitle={Proceedings of the 25th International Conference on Information and
Knowledge Management (CIKM 2016)}, author={Heindorf, Stefan and Potthast, Matthias
and Stein, Benno and Engels, Gregor}, year={2016}, pages={327--336} }'
chicago: Heindorf, Stefan, Matthias Potthast, Benno Stein, and Gregor Engels. “Vandalism
Detection in Wikidata.” In Proceedings of the 25th International Conference
on Information and Knowledge Management (CIKM 2016), 327--336, 2016. https://doi.org/10.1145/2983323.2983740.
ieee: 'S. Heindorf, M. Potthast, B. Stein, and G. Engels, “Vandalism Detection in
Wikidata,” in Proceedings of the 25th International Conference on Information
and Knowledge Management (CIKM 2016), 2016, pp. 327--336, doi: 10.1145/2983323.2983740.'
mla: Heindorf, Stefan, et al. “Vandalism Detection in Wikidata.” Proceedings
of the 25th International Conference on Information and Knowledge Management (CIKM
2016), 2016, pp. 327--336, doi:10.1145/2983323.2983740.
short: 'S. Heindorf, M. Potthast, B. Stein, G. Engels, in: Proceedings of the 25th
International Conference on Information and Knowledge Management (CIKM 2016),
2016, pp. 327--336.'
date_created: 2017-10-17T12:41:18Z
date_updated: 2022-10-17T11:31:41Z
ddc:
- '040'
department:
- _id: '66'
doi: 10.1145/2983323.2983740
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T13:01:43Z
date_updated: 2018-03-21T13:01:43Z
file_id: '1561'
file_name: 137-p327-heindorf.pdf
file_size: 1842753
relation: main_file
success: 1
file_date_updated: 2018-03-21T13:01:43Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/heindorf2016_CIKM.pdf
oa: '1'
page: 327--336
project:
- _id: '1'
name: SFB 901
- _id: '17'
name: SFB 901 - Subprojekt C5
- _id: '4'
name: SFB 901 - Project Area C
publication: Proceedings of the 25th International Conference on Information and Knowledge
Management (CIKM 2016)
status: public
title: Vandalism Detection in Wikidata
type: conference
user_id: '11871'
year: '2016'
...
---
_id: '2978'
author:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
- first_name: Kathrin
full_name: Bujna, Kathrin
last_name: Bujna
citation:
ama: 'Blömer J, Bujna K. Adaptive Seeding for Gaussian Mixture Models. In: Advances
in Knowledge Discovery and Data Mining. Springer International Publishing;
2016:296-308. doi:10.1007/978-3-319-31750-2_24'
apa: Blömer, J., & Bujna, K. (2016). Adaptive Seeding for Gaussian Mixture Models.
In Advances in Knowledge Discovery and Data Mining (pp. 296–308). Springer
International Publishing. https://doi.org/10.1007/978-3-319-31750-2_24
bibtex: '@inbook{Blömer_Bujna_2016, place={Cham}, title={Adaptive Seeding for Gaussian
Mixture Models}, DOI={10.1007/978-3-319-31750-2_24},
booktitle={Advances in Knowledge Discovery and Data Mining}, publisher={Springer
International Publishing}, author={Blömer, Johannes and Bujna, Kathrin}, year={2016},
pages={296–308} }'
chicago: 'Blömer, Johannes, and Kathrin Bujna. “Adaptive Seeding for Gaussian Mixture
Models.” In Advances in Knowledge Discovery and Data Mining, 296–308. Cham:
Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-31750-2_24.'
ieee: 'J. Blömer and K. Bujna, “Adaptive Seeding for Gaussian Mixture Models,” in
Advances in Knowledge Discovery and Data Mining, Cham: Springer International
Publishing, 2016, pp. 296–308.'
mla: Blömer, Johannes, and Kathrin Bujna. “Adaptive Seeding for Gaussian Mixture
Models.” Advances in Knowledge Discovery and Data Mining, Springer International
Publishing, 2016, pp. 296–308, doi:10.1007/978-3-319-31750-2_24.
short: 'J. Blömer, K. Bujna, in: Advances in Knowledge Discovery and Data Mining,
Springer International Publishing, Cham, 2016, pp. 296–308.'
date_created: 2018-06-05T07:31:39Z
date_updated: 2023-01-10T13:49:50Z
department:
- _id: '64'
doi: 10.1007/978-3-319-31750-2_24
page: 296-308
place: Cham
publication: Advances in Knowledge Discovery and Data Mining
publication_identifier:
isbn:
- '9783319317496'
- '9783319317502'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer International Publishing
status: public
title: Adaptive Seeding for Gaussian Mixture Models
type: book_chapter
user_id: '25078'
year: '2016'
...
---
_id: '48306'
abstract:
- lang: eng
text: The goal of argumentation mining, an evolving research field in computational
linguistics, is to design methods capable of analyzing people's argumentation.
In this article, we go beyond the state of the art in several ways. (i) We deal
with actual Web data and take up the challenges given by the variety of registers,
multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We
bridge the gap between normative argumentation theories and argumentation phenomena
encountered in actual data by adapting an argumentation model tested in an extensive
annotation study. (iii) We create a new gold standard corpus (90k tokens in 340
documents) and experiment with several machine learning methods to identify argument
components. We offer the data, source codes, and annotation guidelines to the
community under free licenses. Our findings show that argumentation mining in
user-generated Web discourse is a feasible but challenging task.
author:
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
- first_name: Iryna
full_name: Gurevych, Iryna
last_name: Gurevych
citation:
ama: Habernal I, Gurevych I. Argumentation Mining in User-Generated Web Discourse.
Computational Linguistics. 2016;43(1):125-179. doi:10.1162/coli_a_00276
apa: Habernal, I., & Gurevych, I. (2016). Argumentation Mining in User-Generated
Web Discourse. Computational Linguistics, 43(1), 125–179. https://doi.org/10.1162/coli_a_00276
bibtex: '@article{Habernal_Gurevych_2016, title={Argumentation Mining in User-Generated
Web Discourse}, volume={43}, DOI={10.1162/coli_a_00276},
number={1}, journal={Computational Linguistics}, publisher={MIT Press}, author={Habernal,
Ivan and Gurevych, Iryna}, year={2016}, pages={125–179} }'
chicago: 'Habernal, Ivan, and Iryna Gurevych. “Argumentation Mining in User-Generated
Web Discourse.” Computational Linguistics 43, no. 1 (2016): 125–79. https://doi.org/10.1162/coli_a_00276.'
ieee: 'I. Habernal and I. Gurevych, “Argumentation Mining in User-Generated Web
Discourse,” Computational Linguistics, vol. 43, no. 1, pp. 125–179, 2016,
doi: 10.1162/coli_a_00276.'
mla: Habernal, Ivan, and Iryna Gurevych. “Argumentation Mining in User-Generated
Web Discourse.” Computational Linguistics, vol. 43, no. 1, MIT Press, 2016,
pp. 125–79, doi:10.1162/coli_a_00276.
short: I. Habernal, I. Gurevych, Computational Linguistics 43 (2016) 125–179.
date_created: 2023-10-19T08:30:44Z
date_updated: 2023-10-19T12:08:00Z
department:
- _id: '34'
- _id: '820'
doi: 10.1162/coli_a_00276
intvolume: ' 43'
issue: '1'
keyword:
- Artificial Intelligence
- Computer Science Applications
- Linguistics and Language
- Language and Linguistics
language:
- iso: eng
page: 125-179
publication: Computational Linguistics
publication_identifier:
issn:
- 0891-2017
- 1530-9312
publication_status: published
publisher: MIT Press
status: public
title: Argumentation Mining in User-Generated Web Discourse
type: journal_article
user_id: '15504'
volume: 43
year: '2016'
...
---
_id: '48308'
alternative_title:
- Focused Retrieval Over the Web
author:
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
- first_name: Maria
full_name: Sukhareva, Maria
last_name: Sukhareva
- first_name: Fiana
full_name: Raiber, Fiana
last_name: Raiber
- first_name: Anna
full_name: Shtok, Anna
last_name: Shtok
- first_name: Oren
full_name: Kurland, Oren
last_name: Kurland
- first_name: Hadar
full_name: Ronen, Hadar
last_name: Ronen
- first_name: Judit
full_name: Bar-Ilan, Judit
last_name: Bar-Ilan
- first_name: Iryna
full_name: Gurevych, Iryna
last_name: Gurevych
citation:
ama: 'Habernal I, Sukhareva M, Raiber F, et al. New Collection Announcement. In:
Proceedings of the 39th International ACM SIGIR Conference on Research and
Development in Information Retrieval. ACM; 2016. doi:10.1145/2911451.2914682'
apa: Habernal, I., Sukhareva, M., Raiber, F., Shtok, A., Kurland, O., Ronen, H.,
Bar-Ilan, J., & Gurevych, I. (2016). New Collection Announcement. Proceedings
of the 39th International ACM SIGIR Conference on Research and Development in
Information Retrieval. https://doi.org/10.1145/2911451.2914682
bibtex: '@inproceedings{Habernal_Sukhareva_Raiber_Shtok_Kurland_Ronen_Bar-Ilan_Gurevych_2016,
title={New Collection Announcement}, DOI={10.1145/2911451.2914682},
booktitle={Proceedings of the 39th International ACM SIGIR conference on Research
and Development in Information Retrieval}, publisher={ACM}, author={Habernal,
Ivan and Sukhareva, Maria and Raiber, Fiana and Shtok, Anna and Kurland, Oren
and Ronen, Hadar and Bar-Ilan, Judit and Gurevych, Iryna}, year={2016} }'
chicago: Habernal, Ivan, Maria Sukhareva, Fiana Raiber, Anna Shtok, Oren Kurland,
Hadar Ronen, Judit Bar-Ilan, and Iryna Gurevych. “New Collection Announcement.”
In Proceedings of the 39th International ACM SIGIR Conference on Research and
Development in Information Retrieval. ACM, 2016. https://doi.org/10.1145/2911451.2914682.
ieee: 'I. Habernal et al., “New Collection Announcement,” 2016, doi: 10.1145/2911451.2914682.'
mla: Habernal, Ivan, et al. “New Collection Announcement.” Proceedings of the
39th International ACM SIGIR Conference on Research and Development in Information
Retrieval, ACM, 2016, doi:10.1145/2911451.2914682.
short: 'I. Habernal, M. Sukhareva, F. Raiber, A. Shtok, O. Kurland, H. Ronen, J.
Bar-Ilan, I. Gurevych, in: Proceedings of the 39th International ACM SIGIR Conference
on Research and Development in Information Retrieval, ACM, 2016.'
date_created: 2023-10-19T08:31:35Z
date_updated: 2023-10-19T12:07:25Z
department:
- _id: '34'
- _id: '820'
doi: 10.1145/2911451.2914682
language:
- iso: eng
publication: Proceedings of the 39th International ACM SIGIR conference on Research
and Development in Information Retrieval
publication_status: published
publisher: ACM
status: public
title: New Collection Announcement
type: conference
user_id: '15504'
year: '2016'
...
---
_id: '48307'
author:
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
- first_name: Iryna
full_name: Gurevych, Iryna
last_name: Gurevych
citation:
ama: 'Habernal I, Gurevych I. Which argument is more convincing? Analyzing and predicting
convincingness of Web arguments using bidirectional LSTM. In: Proceedings of
the 54th Annual Meeting of the Association for Computational Linguistics (Volume
1: Long Papers). Association for Computational Linguistics; 2016. doi:10.18653/v1/p16-1150'
apa: 'Habernal, I., & Gurevych, I. (2016). Which argument is more convincing?
Analyzing and predicting convincingness of Web arguments using bidirectional LSTM.
Proceedings of the 54th Annual Meeting of the Association for Computational
Linguistics (Volume 1: Long Papers). https://doi.org/10.18653/v1/p16-1150'
bibtex: '@inproceedings{Habernal_Gurevych_2016, title={Which argument is more convincing?
Analyzing and predicting convincingness of Web arguments using bidirectional LSTM},
DOI={10.18653/v1/p16-1150},
booktitle={Proceedings of the 54th Annual Meeting of the Association for Computational
Linguistics (Volume 1: Long Papers)}, publisher={Association for Computational
Linguistics}, author={Habernal, Ivan and Gurevych, Iryna}, year={2016} }'
chicago: 'Habernal, Ivan, and Iryna Gurevych. “Which Argument Is More Convincing?
Analyzing and Predicting Convincingness of Web Arguments Using Bidirectional LSTM.”
In Proceedings of the 54th Annual Meeting of the Association for Computational
Linguistics (Volume 1: Long Papers). Association for Computational Linguistics,
2016. https://doi.org/10.18653/v1/p16-1150.'
ieee: 'I. Habernal and I. Gurevych, “Which argument is more convincing? Analyzing
and predicting convincingness of Web arguments using bidirectional LSTM,” 2016,
doi: 10.18653/v1/p16-1150.'
mla: 'Habernal, Ivan, and Iryna Gurevych. “Which Argument Is More Convincing? Analyzing
and Predicting Convincingness of Web Arguments Using Bidirectional LSTM.” Proceedings
of the 54th Annual Meeting of the Association for Computational Linguistics (Volume
1: Long Papers), Association for Computational Linguistics, 2016, doi:10.18653/v1/p16-1150.'
short: 'I. Habernal, I. Gurevych, in: Proceedings of the 54th Annual Meeting of
the Association for Computational Linguistics (Volume 1: Long Papers), Association
for Computational Linguistics, 2016.'
date_created: 2023-10-19T08:31:11Z
date_updated: 2023-10-19T12:07:44Z
department:
- _id: '34'
- _id: '820'
doi: 10.18653/v1/p16-1150
language:
- iso: eng
publication: 'Proceedings of the 54th Annual Meeting of the Association for Computational
Linguistics (Volume 1: Long Papers)'
publication_status: published
publisher: Association for Computational Linguistics
status: public
title: Which argument is more convincing? Analyzing and predicting convincingness
of Web arguments using bidirectional LSTM
type: conference
user_id: '15504'
year: '2016'
...
---
_id: '46364'
abstract:
- lang: eng
text: Automated algorithm configuration procedures play an increasingly important
role in the development and application of algorithms for a wide range of computationally
challenging problems. Until very recently, these configuration procedures were
limited to optimising a single performance objective, such as the running time
or solution quality achieved by the algorithm being configured. However, in many
applications there is more than one performance objective of interest. This gives
rise to the multi-objective automatic algorithm configuration problem, which involves
finding a Pareto set of configurations of a given target algorithm that characterises
trade-offs between multiple performance objectives. In this work, we introduce
MO-ParamILS, a multi-objective extension of the state-of-the-art single-objective
algorithm configuration framework ParamILS, and demonstrate that it produces good
results on several challenging bi-objective algorithm configuration scenarios
compared to a base-line obtained from using a state-of-the-art single-objective
algorithm configurator.
author:
- first_name: A
full_name: Blot, A
last_name: Blot
- first_name: H
full_name: Hoos, H
last_name: Hoos
- first_name: L
full_name: Jourdan, L
last_name: Jourdan
- first_name: M
full_name: Marmion, M
last_name: Marmion
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Blot A, Hoos H, Jourdan L, Marmion M, Trautmann H. MO-ParamILS: A Multi-objective
Automatic Algorithm Configuration Framework. In: et al. Joaquin V, ed. LION
2016: Learning and Intelligent Optimization. Vol 10079. LNTCS. Springer International
Publishing; 2016:32–47. doi:10.1007/978-3-319-50349-3_3'
apa: 'Blot, A., Hoos, H., Jourdan, L., Marmion, M., & Trautmann, H. (2016).
MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework. In
V. et al. Joaquin (Ed.), LION 2016: Learning and Intelligent Optimization
(Vol. 10079, pp. 32–47). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_3'
bibtex: '@inproceedings{Blot_Hoos_Jourdan_Marmion_Trautmann_2016, place={Cham},
series={LNTCS}, title={MO-ParamILS: A Multi-objective Automatic Algorithm Configuration
Framework}, volume={10079}, DOI={10.1007/978-3-319-50349-3_3},
booktitle={LION 2016: Learning and Intelligent Optimization}, publisher={Springer
International Publishing}, author={Blot, A and Hoos, H and Jourdan, L and Marmion,
M and Trautmann, Heike}, editor={et al. Joaquin, Vanschooren}, year={2016}, pages={32–47},
collection={LNTCS} }'
chicago: 'Blot, A, H Hoos, L Jourdan, M Marmion, and Heike Trautmann. “MO-ParamILS:
A Multi-Objective Automatic Algorithm Configuration Framework.” In LION 2016:
Learning and Intelligent Optimization, edited by Vanschooren et al. Joaquin,
10079:32–47. LNTCS. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-50349-3_3.'
ieee: 'A. Blot, H. Hoos, L. Jourdan, M. Marmion, and H. Trautmann, “MO-ParamILS:
A Multi-objective Automatic Algorithm Configuration Framework,” in LION 2016:
Learning and Intelligent Optimization, 2016, vol. 10079, pp. 32–47, doi: 10.1007/978-3-319-50349-3_3.'
mla: 'Blot, A., et al. “MO-ParamILS: A Multi-Objective Automatic Algorithm Configuration
Framework.” LION 2016: Learning and Intelligent Optimization, edited by
Vanschooren et al. Joaquin, vol. 10079, Springer International Publishing, 2016,
pp. 32–47, doi:10.1007/978-3-319-50349-3_3.'
short: 'A. Blot, H. Hoos, L. Jourdan, M. Marmion, H. Trautmann, in: V. et al. Joaquin
(Ed.), LION 2016: Learning and Intelligent Optimization, Springer International
Publishing, Cham, 2016, pp. 32–47.'
date_created: 2023-08-04T15:10:09Z
date_updated: 2023-10-16T13:37:50Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-319-50349-3_3
editor:
- first_name: Vanschooren
full_name: et al. Joaquin, Vanschooren
last_name: et al. Joaquin
intvolume: ' 10079'
language:
- iso: eng
page: 32–47
place: Cham
publication: 'LION 2016: Learning and Intelligent Optimization'
publisher: Springer International Publishing
series_title: LNTCS
status: public
title: 'MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework'
type: conference
user_id: '15504'
volume: 10079
year: '2016'
...
---
_id: '46363'
abstract:
- lang: eng
text: "The averaged Hausdorff distance has been proposed as an indicator for assessing
the quality of finitely sized approximations of the Pareto front of a multiobjective
problem. Since many set-based, iterative optimization algorithms store their currently
best approximation in an internal archive these approximations are also termed
archives. In case of two objectives and continuous variables it is known that
the best approximations in terms of averaged Hausdorff distance are subsets of
the Pareto front if it is concave. If it is linear or circularly concave the points
of the best approximation are equally spaced.\r\n\r\nHere, it is proven that the
optimal averaged Hausdorff approximation and the Pareto front have an empty intersection
if the Pareto front is circularly convex. But the points of the best approximation
are equally spaced and they rapidly approach the Pareto front for increasing size
of the approximation."
author:
- first_name: G
full_name: Rudolph, G
last_name: Rudolph
- first_name: O
full_name: Schütze, O
last_name: Schütze
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Rudolph G, Schütze O, Trautmann H. On the Closest Averaged Hausdorff Archive
for a Circularly Convex Pareto Front. In: Squillero G, Burelli P, eds. Applications
of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016,
Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II. Springer
International Publishing; 2016:42–55. doi:10.1007/978-3-319-31153-1_4'
apa: 'Rudolph, G., Schütze, O., & Trautmann, H. (2016). On the Closest Averaged
Hausdorff Archive for a Circularly Convex Pareto Front. In G. Squillero &
P. Burelli (Eds.), Applications of Evolutionary Computation: 19$^th$ European
Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings,
Part II (pp. 42–55). Springer International Publishing. https://doi.org/10.1007/978-3-319-31153-1_4'
bibtex: '@inbook{Rudolph_Schütze_Trautmann_2016, place={Cham}, title={On the Closest
Averaged Hausdorff Archive for a Circularly Convex Pareto Front}, DOI={10.1007/978-3-319-31153-1_4},
booktitle={Applications of Evolutionary Computation: 19$^th$ European Conference,
EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings,
Part II}, publisher={Springer International Publishing}, author={Rudolph, G and
Schütze, O and Trautmann, Heike}, editor={Squillero, G and Burelli, P}, year={2016},
pages={42–55} }'
chicago: 'Rudolph, G, O Schütze, and Heike Trautmann. “On the Closest Averaged Hausdorff
Archive for a Circularly Convex Pareto Front.” In Applications of Evolutionary
Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal,
March 30 — April 1, 2016, Proceedings, Part II, edited by G Squillero and
P Burelli, 42–55. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-31153-1_4.'
ieee: 'G. Rudolph, O. Schütze, and H. Trautmann, “On the Closest Averaged Hausdorff
Archive for a Circularly Convex Pareto Front,” in Applications of Evolutionary
Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal,
March 30 — April 1, 2016, Proceedings, Part II, G. Squillero and P. Burelli,
Eds. Cham: Springer International Publishing, 2016, pp. 42–55.'
mla: 'Rudolph, G., et al. “On the Closest Averaged Hausdorff Archive for a Circularly
Convex Pareto Front.” Applications of Evolutionary Computation: 19$^th$ European
Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings,
Part II, edited by G Squillero and P Burelli, Springer International Publishing,
2016, pp. 42–55, doi:10.1007/978-3-319-31153-1_4.'
short: 'G. Rudolph, O. Schütze, H. Trautmann, in: G. Squillero, P. Burelli (Eds.),
Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications
2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II, Springer
International Publishing, Cham, 2016, pp. 42–55.'
date_created: 2023-08-04T15:09:14Z
date_updated: 2023-10-16T13:37:33Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-319-31153-1_4
editor:
- first_name: G
full_name: Squillero, G
last_name: Squillero
- first_name: P
full_name: Burelli, P
last_name: Burelli
language:
- iso: eng
page: 42–55
place: Cham
publication: 'Applications of Evolutionary Computation: 19$^th$ European Conference,
EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part
II'
publication_identifier:
isbn:
- 978-3-319-31153-1
publisher: Springer International Publishing
status: public
title: On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front
type: book_chapter
user_id: '15504'
year: '2016'
...
---
_id: '46369'
abstract:
- lang: eng
text: This paper formally defines multimodality in multiobjective optimization (MO).
We introduce a test-bed in which multimodal MO problems with known properties
can be constructed as well as numerical characteristics of the resulting landscape.
Gradient- and local search based strategies are compared on exemplary problems
together with specific performance indicators in the multimodal MO setting. By
this means the foundation for Exploratory Landscape Analysis in MO is provided.
author:
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Hao
full_name: Wang, Hao
last_name: Wang
- first_name: Mike
full_name: Preuss, Mike
last_name: Preuss
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: André
full_name: Deutz, André
last_name: Deutz
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Michael
full_name: Emmerich, Michael
last_name: Emmerich
citation:
ama: 'Kerschke P, Wang H, Preuss M, et al. Towards Analyzing Multimodality of Multiobjective
Landscapes. In: Proceedings of the 14$^th$ International Conference on Parallel
Problem Solving from Nature (PPSN XIV). Lecture Notes in Computer Science.
Springer; 2016:962–972. doi:10.1007/978-3-319-45823-6_90'
apa: Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., &
Emmerich, M. (2016). Towards Analyzing Multimodality of Multiobjective Landscapes.
Proceedings of the 14$^th$ International Conference on Parallel Problem Solving
from Nature (PPSN XIV), 962–972. https://doi.org/10.1007/978-3-319-45823-6_90
bibtex: '@inproceedings{Kerschke_Wang_Preuss_Grimme_Deutz_Trautmann_Emmerich_2016,
place={Edinburgh, Scotland}, series={Lecture Notes in Computer Science}, title={Towards
Analyzing Multimodality of Multiobjective Landscapes}, DOI={10.1007/978-3-319-45823-6_90},
booktitle={Proceedings of the 14$^th$ International Conference on Parallel Problem
Solving from Nature (PPSN XIV)}, publisher={Springer}, author={Kerschke, Pascal
and Wang, Hao and Preuss, Mike and Grimme, Christian and Deutz, André and Trautmann,
Heike and Emmerich, Michael}, year={2016}, pages={962–972}, collection={Lecture
Notes in Computer Science} }'
chicago: 'Kerschke, Pascal, Hao Wang, Mike Preuss, Christian Grimme, André Deutz,
Heike Trautmann, and Michael Emmerich. “Towards Analyzing Multimodality of Multiobjective
Landscapes.” In Proceedings of the 14$^th$ International Conference on Parallel
Problem Solving from Nature (PPSN XIV), 962–972. Lecture Notes in Computer
Science. Edinburgh, Scotland: Springer, 2016. https://doi.org/10.1007/978-3-319-45823-6_90.'
ieee: 'P. Kerschke et al., “Towards Analyzing Multimodality of Multiobjective
Landscapes,” in Proceedings of the 14$^th$ International Conference on Parallel
Problem Solving from Nature (PPSN XIV), 2016, pp. 962–972, doi: 10.1007/978-3-319-45823-6_90.'
mla: Kerschke, Pascal, et al. “Towards Analyzing Multimodality of Multiobjective
Landscapes.” Proceedings of the 14$^th$ International Conference on Parallel
Problem Solving from Nature (PPSN XIV), Springer, 2016, pp. 962–972, doi:10.1007/978-3-319-45823-6_90.
short: 'P. Kerschke, H. Wang, M. Preuss, C. Grimme, A. Deutz, H. Trautmann, M. Emmerich,
in: Proceedings of the 14$^th$ International Conference on Parallel Problem Solving
from Nature (PPSN XIV), Springer, Edinburgh, Scotland, 2016, pp. 962–972.'
date_created: 2023-08-04T15:16:02Z
date_updated: 2023-10-16T13:39:42Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-319-45823-6_90
language:
- iso: eng
page: 962–972
place: Edinburgh, Scotland
publication: Proceedings of the 14$^th$ International Conference on Parallel Problem
Solving from Nature (PPSN XIV)
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Towards Analyzing Multimodality of Multiobjective Landscapes
type: conference
user_id: '15504'
year: '2016'
...
---
_id: '46367'
abstract:
- lang: eng
text: When selecting the best suited algorithm for an unknown optimization problem,
it is useful to possess some a priori knowledge of the problem at hand. In the
context of single-objective, continuous optimization problems such knowledge can
be retrieved by means of Exploratory Landscape Analysis (ELA), which automatically
identifies properties of a landscape, e.g., the so-called funnel structures, based
on an initial sample. In this paper, we extract the relevant features (for detecting
funnels) out of a large set of landscape features when only given a small initial
sample consisting of 50 x D observations, where D is the number of decision space
dimensions. This is already in the range of the start population sizes of many
evolutionary algorithms. The new Multiple Peaks Model Generator (MPM2) is used
for training the classifier, and the approach is then very successfully validated
on the Black-Box Optimization Benchmark (BBOB) and a subset of the CEC 2013 niching
competition problems.
author:
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Mike
full_name: Preuss, Mike
last_name: Preuss
- first_name: Simon
full_name: Wessing, Simon
last_name: Wessing
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Kerschke P, Preuss M, Wessing S, Trautmann H. Low-Budget Exploratory Landscape
Analysis on Multiple Peaks Models. In: Proceedings of the 18$^th$ Annual Conference
on Genetic and Evolutionary Computation. ; 2016:229–236. doi:10.1145/2908812.2908845'
apa: Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2016). Low-Budget
Exploratory Landscape Analysis on Multiple Peaks Models. Proceedings of the
18$^th$ Annual Conference on Genetic and Evolutionary Computation, 229–236.
https://doi.org/10.1145/2908812.2908845
bibtex: '@inproceedings{Kerschke_Preuss_Wessing_Trautmann_2016, place={Denver, CO,
USA}, title={Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models},
DOI={10.1145/2908812.2908845},
booktitle={Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary
Computation}, author={Kerschke, Pascal and Preuss, Mike and Wessing, Simon and
Trautmann, Heike}, year={2016}, pages={229–236} }'
chicago: Kerschke, Pascal, Mike Preuss, Simon Wessing, and Heike Trautmann. “Low-Budget
Exploratory Landscape Analysis on Multiple Peaks Models.” In Proceedings of
the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, 229–236.
Denver, CO, USA, 2016. https://doi.org/10.1145/2908812.2908845.
ieee: 'P. Kerschke, M. Preuss, S. Wessing, and H. Trautmann, “Low-Budget Exploratory
Landscape Analysis on Multiple Peaks Models,” in Proceedings of the 18$^th$
Annual Conference on Genetic and Evolutionary Computation, 2016, pp. 229–236,
doi: 10.1145/2908812.2908845.'
mla: Kerschke, Pascal, et al. “Low-Budget Exploratory Landscape Analysis on Multiple
Peaks Models.” Proceedings of the 18$^th$ Annual Conference on Genetic and
Evolutionary Computation, 2016, pp. 229–236, doi:10.1145/2908812.2908845.
short: 'P. Kerschke, M. Preuss, S. Wessing, H. Trautmann, in: Proceedings of the
18$^th$ Annual Conference on Genetic and Evolutionary Computation, Denver, CO,
USA, 2016, pp. 229–236.'
date_created: 2023-08-04T15:14:06Z
date_updated: 2023-10-16T13:38:47Z
department:
- _id: '34'
- _id: '819'
doi: 10.1145/2908812.2908845
language:
- iso: eng
page: 229–236
place: Denver, CO, USA
publication: Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary
Computation
publication_identifier:
isbn:
- 978-1-4503-4206-3
status: public
title: Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models
type: conference
user_id: '15504'
year: '2016'
...
---
_id: '46371'
abstract:
- lang: eng
text: "One main task in evolutionary multiobjective optimization (EMO) is to obtain
a suitable finite size approximation of the Pareto front which is the image of
the solution set, termed the Pareto set, of a given multiobjective optimization
problem. In the technical literature, the characteristic of the desired approximation
is commonly expressed by closeness to the Pareto front and a sufficient spread
of the solutions obtained. In this paper, we first make an effort to show by theoretical
and empirical findings that the recently proposed Averaged Hausdorff (or Δ\U0001D45D-)
indicator indeed aims at fulfilling both performance criteria for bi-objective
optimization problems. In the second part of this paper, standard EMO algorithms
combined with a specialized archiver and a postprocessing step based on the Δ\U0001D45D
indicator are introduced which sufficiently approximate the Δ\U0001D45D-optimal
archives and generate solutions evenly spread along the Pareto front."
author:
- first_name: G
full_name: Rudolph, G
last_name: Rudolph
- first_name: O
full_name: Schütze, O
last_name: Schütze
- first_name: C
full_name: Grimme, C
last_name: Grimme
- first_name: C
full_name: Domínguez-Medina, C
last_name: Domínguez-Medina
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Rudolph G, Schütze O, Grimme C, Domínguez-Medina C, Trautmann H. Optimal averaged
Hausdorff archives for bi-objective problems: theoretical and numerical results.
Computational Optimization and Applications (Comput Optim Appl). 2016;64(2):589–618.
doi:10.1007/s10589-015-9815-8'
apa: 'Rudolph, G., Schütze, O., Grimme, C., Domínguez-Medina, C., & Trautmann,
H. (2016). Optimal averaged Hausdorff archives for bi-objective problems: theoretical
and numerical results. Computational Optimization and Applications (Comput.
Optim. Appl.), 64(2), 589–618. https://doi.org/10.1007/s10589-015-9815-8'
bibtex: '@article{Rudolph_Schütze_Grimme_Domínguez-Medina_Trautmann_2016, title={Optimal
averaged Hausdorff archives for bi-objective problems: theoretical and numerical
results}, volume={64}, DOI={10.1007/s10589-015-9815-8},
number={2}, journal={Computational Optimization and Applications (Comput. Optim.
Appl.)}, author={Rudolph, G and Schütze, O and Grimme, C and Domínguez-Medina,
C and Trautmann, Heike}, year={2016}, pages={589–618} }'
chicago: 'Rudolph, G, O Schütze, C Grimme, C Domínguez-Medina, and Heike Trautmann.
“Optimal Averaged Hausdorff Archives for Bi-Objective Problems: Theoretical and
Numerical Results.” Computational Optimization and Applications (Comput. Optim.
Appl.) 64, no. 2 (2016): 589–618. https://doi.org/10.1007/s10589-015-9815-8.'
ieee: 'G. Rudolph, O. Schütze, C. Grimme, C. Domínguez-Medina, and H. Trautmann,
“Optimal averaged Hausdorff archives for bi-objective problems: theoretical and
numerical results,” Computational Optimization and Applications (Comput. Optim.
Appl.), vol. 64, no. 2, pp. 589–618, 2016, doi: 10.1007/s10589-015-9815-8.'
mla: 'Rudolph, G., et al. “Optimal Averaged Hausdorff Archives for Bi-Objective
Problems: Theoretical and Numerical Results.” Computational Optimization and
Applications (Comput. Optim. Appl.), vol. 64, no. 2, 2016, pp. 589–618, doi:10.1007/s10589-015-9815-8.'
short: G. Rudolph, O. Schütze, C. Grimme, C. Domínguez-Medina, H. Trautmann, Computational
Optimization and Applications (Comput. Optim. Appl.) 64 (2016) 589–618.
date_created: 2023-08-04T15:17:48Z
date_updated: 2023-10-16T13:40:21Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/s10589-015-9815-8
intvolume: ' 64'
issue: '2'
language:
- iso: eng
page: 589–618
publication: Computational Optimization and Applications (Comput. Optim. Appl.)
status: public
title: 'Optimal averaged Hausdorff archives for bi-objective problems: theoretical
and numerical results'
type: journal_article
user_id: '15504'
volume: 64
year: '2016'
...
---
_id: '46372'
abstract:
- lang: eng
text: We present a new hybrid evolutionary algorithm for the effective hypervolume
approximation of the Pareto front of a given differentiable multi-objective optimization
problem. Starting point for the local search (LS) mechanism is a new division
of the decision space as we will argue that in each of these regions a different
LS strategy seems to be most promising. For the LS in two out of the three regions
we will utilize and adapt the Directed Search method which is capable of steering
the search into any direction given in objective space and which is thus well
suited for the problem at hand. We further on integrate the resulting LS mechanism
into SMS-EMOA, a state-of-the-art evolutionary algorithm for hypervolume approximations.
Finally, we will present some numerical results on several benchmark problems
with two and three objectives indicating the strength and competitiveness of the
novel hybrid.
author:
- first_name: O
full_name: Schütze, O
last_name: Schütze
- first_name: Hernandez VA
full_name: Sosa, Hernandez VA
last_name: Sosa
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: G
full_name: Rudolph, G
last_name: Rudolph
citation:
ama: Schütze O, Sosa HV, Trautmann H, Rudolph G. The Hypervolume based Directed
Search Method for Multi-Objective Optimization Problems. Journal of Heuristics.
2016;22(3):273–300. doi:10.1007/s10732-016-9310-0
apa: Schütze, O., Sosa, H. V., Trautmann, H., & Rudolph, G. (2016). The Hypervolume
based Directed Search Method for Multi-Objective Optimization Problems. Journal
of Heuristics, 22(3), 273–300. https://doi.org/10.1007/s10732-016-9310-0
bibtex: '@article{Schütze_Sosa_Trautmann_Rudolph_2016, title={The Hypervolume based
Directed Search Method for Multi-Objective Optimization Problems}, volume={22},
DOI={10.1007/s10732-016-9310-0},
number={3}, journal={Journal of Heuristics}, author={Schütze, O and Sosa, Hernandez
VA and Trautmann, Heike and Rudolph, G}, year={2016}, pages={273–300} }'
chicago: 'Schütze, O, Hernandez VA Sosa, Heike Trautmann, and G Rudolph. “The Hypervolume
Based Directed Search Method for Multi-Objective Optimization Problems.” Journal
of Heuristics 22, no. 3 (2016): 273–300. https://doi.org/10.1007/s10732-016-9310-0.'
ieee: 'O. Schütze, H. V. Sosa, H. Trautmann, and G. Rudolph, “The Hypervolume based
Directed Search Method for Multi-Objective Optimization Problems,” Journal
of Heuristics, vol. 22, no. 3, pp. 273–300, 2016, doi: 10.1007/s10732-016-9310-0.'
mla: Schütze, O., et al. “The Hypervolume Based Directed Search Method for Multi-Objective
Optimization Problems.” Journal of Heuristics, vol. 22, no. 3, 2016, pp.
273–300, doi:10.1007/s10732-016-9310-0.
short: O. Schütze, H.V. Sosa, H. Trautmann, G. Rudolph, Journal of Heuristics 22
(2016) 273–300.
date_created: 2023-08-04T15:19:11Z
date_updated: 2023-10-16T13:40:43Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/s10732-016-9310-0
intvolume: ' 22'
issue: '3'
language:
- iso: eng
page: 273–300
publication: Journal of Heuristics
status: public
title: The Hypervolume based Directed Search Method for Multi-Objective Optimization
Problems
type: journal_article
user_id: '15504'
volume: 22
year: '2016'
...
---
_id: '46368'
abstract:
- lang: eng
text: Exploratory Landscape Analysis (ELA) aims at understanding characteristics
of single-objective continuous (black-box) optimization problems in an automated
way. Moreover, the approach provides the basis for constructing algorithm selection
models for unseen problem instances. Recently, it has gained increasing attention
and numerical features have been designed by various research groups. This paper
introduces the R-Package FLACCO which makes all relevant features available in
a unified framework together with efficient helper functions. Moreover, a case
study which gives perspectives to ELA for multi-objective optimization problems
is presented.
author:
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Kerschke P, Trautmann H. The R-Package FLACCO for Exploratory Landscape Analysis
with Applications to Multi-Objective Optimization Problems. In: Proceedings
of the IEEE Congress on Evolutionary Computation (CEC). ; 2016. doi:10.1109/CEC.2016.7748359'
apa: Kerschke, P., & Trautmann, H. (2016). The R-Package FLACCO for Exploratory
Landscape Analysis with Applications to Multi-Objective Optimization Problems.
Proceedings of the IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2016.7748359
bibtex: '@inproceedings{Kerschke_Trautmann_2016, place={Vancouver, BC, Kanada},
title={The R-Package FLACCO for Exploratory Landscape Analysis with Applications
to Multi-Objective Optimization Problems}, DOI={10.1109/CEC.2016.7748359},
booktitle={Proceedings of the IEEE Congress on Evolutionary Computation (CEC)},
author={Kerschke, Pascal and Trautmann, Heike}, year={2016} }'
chicago: Kerschke, Pascal, and Heike Trautmann. “The R-Package FLACCO for Exploratory
Landscape Analysis with Applications to Multi-Objective Optimization Problems.”
In Proceedings of the IEEE Congress on Evolutionary Computation (CEC).
Vancouver, BC, Kanada, 2016. https://doi.org/10.1109/CEC.2016.7748359.
ieee: 'P. Kerschke and H. Trautmann, “The R-Package FLACCO for Exploratory Landscape
Analysis with Applications to Multi-Objective Optimization Problems,” 2016, doi:
10.1109/CEC.2016.7748359.'
mla: Kerschke, Pascal, and Heike Trautmann. “The R-Package FLACCO for Exploratory
Landscape Analysis with Applications to Multi-Objective Optimization Problems.”
Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2016,
doi:10.1109/CEC.2016.7748359.
short: 'P. Kerschke, H. Trautmann, in: Proceedings of the IEEE Congress on Evolutionary
Computation (CEC), Vancouver, BC, Kanada, 2016.'
date_created: 2023-08-04T15:14:52Z
date_updated: 2023-10-16T13:39:06Z
department:
- _id: '34'
- _id: '819'
doi: 10.1109/CEC.2016.7748359
language:
- iso: eng
place: Vancouver, BC, Kanada
publication: Proceedings of the IEEE Congress on Evolutionary Computation (CEC)
status: public
title: The R-Package FLACCO for Exploratory Landscape Analysis with Applications to
Multi-Objective Optimization Problems
type: conference
user_id: '15504'
year: '2016'
...
---
_id: '46370'
abstract:
- lang: eng
text: This report documents the talks and discussions at the Dagstuhl Seminar 15211
"Theory of Evolutionary Algorithms". This seminar, now in its 8th edition, is
the main meeting point of the highly active theory of randomized search heuristics
subcommunities in Australia, Asia, North America, and Europe. Topics intensively
discussed include rigorous runtime analysis and computational complexity theory
for randomised search heuristics, information geometry of randomised search, and
synergies between the theory of evolutionary algorithms and theories of natural
evolution.
author:
- first_name: F
full_name: Neumann, F
last_name: Neumann
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Neumann F, Trautmann H. Working Group Report: Bridging the Gap Between Experiments
and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms
(Dagstuhl Seminar 15211). Dagstuhl Reports. 2016;5(5):78–79. doi:10.4230/DagRep.5.5.57'
apa: 'Neumann, F., & Trautmann, H. (2016). Working Group Report: Bridging the
Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory
of Evolutionary Algorithms (Dagstuhl Seminar 15211). Dagstuhl Reports,
5(5), 78–79. https://doi.org/10.4230/DagRep.5.5.57'
bibtex: '@article{Neumann_Trautmann_2016, title={Working Group Report: Bridging
the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis;
Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211)}, volume={5}, DOI={10.4230/DagRep.5.5.57}, number={5},
journal={Dagstuhl Reports}, author={Neumann, F and Trautmann, Heike}, year={2016},
pages={78–79} }'
chicago: 'Neumann, F, and Heike Trautmann. “Working Group Report: Bridging the Gap
Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of
Evolutionary Algorithms (Dagstuhl Seminar 15211).” Dagstuhl Reports 5,
no. 5 (2016): 78–79. https://doi.org/10.4230/DagRep.5.5.57.'
ieee: 'F. Neumann and H. Trautmann, “Working Group Report: Bridging the Gap Between
Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary
Algorithms (Dagstuhl Seminar 15211),” Dagstuhl Reports, vol. 5, no. 5,
pp. 78–79, 2016, doi: 10.4230/DagRep.5.5.57.'
mla: 'Neumann, F., and Heike Trautmann. “Working Group Report: Bridging the Gap
Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of
Evolutionary Algorithms (Dagstuhl Seminar 15211).” Dagstuhl Reports, vol.
5, no. 5, 2016, pp. 78–79, doi:10.4230/DagRep.5.5.57.'
short: F. Neumann, H. Trautmann, Dagstuhl Reports 5 (2016) 78–79.
date_created: 2023-08-04T15:17:00Z
date_updated: 2023-10-16T13:40:00Z
department:
- _id: '34'
- _id: '819'
doi: 10.4230/DagRep.5.5.57
intvolume: ' 5'
issue: '5'
language:
- iso: eng
page: 78–79
publication: Dagstuhl Reports
status: public
title: 'Working Group Report: Bridging the Gap Between Experiments and Theory Using
Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar
15211)'
type: journal_article
user_id: '15504'
volume: 5
year: '2016'
...
---
_id: '48309'
author:
- first_name: Ivan
full_name: Habernal, Ivan
id: '101881'
last_name: Habernal
- first_name: Iryna
full_name: Gurevych, Iryna
last_name: Gurevych
citation:
ama: 'Habernal I, Gurevych I. What makes a convincing argument? Empirical analysis
and detecting attributes of convincingness in Web argumentation. In:
Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing. Association for Computational Linguistics; 2016. doi:10.18653/v1/d16-1129'
apa: Habernal, I., & Gurevych, I. (2016). What makes a convincing argument?
Empirical analysis and detecting attributes of convincingness in Web
argumentation. Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing. https://doi.org/10.18653/v1/d16-1129
bibtex: '@inproceedings{Habernal_Gurevych_2016, title={What makes a convincing argument?
Empirical analysis and detecting attributes of convincingness in Web
argumentation}, DOI={10.18653/v1/d16-1129},
booktitle={Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing}, publisher={Association for Computational Linguistics},
author={Habernal, Ivan and Gurevych, Iryna}, year={2016} }'
chicago: Habernal, Ivan, and Iryna Gurevych. “What Makes a Convincing Argument?
Empirical Analysis and Detecting Attributes of Convincingness in Web
Argumentation.” In Proceedings of the 2016 Conference on Empirical Methods
in Natural Language Processing. Association for Computational Linguistics,
2016. https://doi.org/10.18653/v1/d16-1129.
ieee: 'I. Habernal and I. Gurevych, “What makes a convincing argument? Empirical
analysis and detecting attributes of convincingness in Web argumentation,”
2016, doi: 10.18653/v1/d16-1129.'
mla: Habernal, Ivan, and Iryna Gurevych. “What Makes a Convincing Argument? Empirical
Analysis and Detecting Attributes of Convincingness in Web Argumentation.”
Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing, Association for Computational Linguistics, 2016, doi:10.18653/v1/d16-1129.
short: 'I. Habernal, I. Gurevych, in: Proceedings of the 2016 Conference on Empirical
Methods in Natural Language Processing, Association for Computational
Linguistics, 2016.'
date_created: 2023-10-19T08:31:58Z
date_updated: 2023-10-19T12:07:05Z
department:
- _id: '34'
- _id: '820'
doi: 10.18653/v1/d16-1129
language:
- iso: eng
publication: Proceedings of the 2016 Conference on Empirical Methods in Natural Language
Processing
publication_status: published
publisher: Association for Computational Linguistics
status: public
title: What makes a convincing argument? Empirical analysis and detecting attributes
of convincingness in Web argumentation
type: conference
user_id: '15504'
year: '2016'
...
---
_id: '48873'
abstract:
- lang: eng
text: Despite the intrinsic hardness of the Traveling Salesperson Problem (TSP)
heuristic solvers, e.g., LKH+restart and EAX+restart, are remarkably successful
in generating satisfactory or even optimal solutions. However, the reasons for
their success are not yet fully understood. Recent approaches take an analytical
viewpoint and try to identify instance features, which make an instance hard or
easy to solve. We contribute to this area by generating instance sets for couples
of TSP algorithms A and B by maximizing/minimizing their performance difference
in order to generate instances which are easier to solve for one solver and much
harder to solve for the other. This instance set offers the potential to identify
key features which allow to distinguish between the problem hardness classes of
both algorithms.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Bossek J, Trautmann H. Evolving Instances for Maximizing Performance Differences
of State-of-the-Art Inexact TSP Solvers. In: Festa P, Sellmann M, Vanschoren J,
eds. Learning and Intelligent Optimization. Lecture Notes in Computer Science.
Springer International Publishing; 2016:48–59. doi:10.1007/978-3-319-50349-3_4'
apa: Bossek, J., & Trautmann, H. (2016). Evolving Instances for Maximizing Performance
Differences of State-of-the-Art Inexact TSP Solvers. In P. Festa, M. Sellmann,
& J. Vanschoren (Eds.), Learning and Intelligent Optimization (pp.
48–59). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_4
bibtex: '@inproceedings{Bossek_Trautmann_2016, place={Cham}, series={Lecture Notes
in Computer Science}, title={Evolving Instances for Maximizing Performance Differences
of State-of-the-Art Inexact TSP Solvers}, DOI={10.1007/978-3-319-50349-3_4},
booktitle={Learning and Intelligent Optimization}, publisher={Springer International
Publishing}, author={Bossek, Jakob and Trautmann, Heike}, editor={Festa, Paola
and Sellmann, Meinolf and Vanschoren, Joaquin}, year={2016}, pages={48–59}, collection={Lecture
Notes in Computer Science} }'
chicago: 'Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing
Performance Differences of State-of-the-Art Inexact TSP Solvers.” In Learning
and Intelligent Optimization, edited by Paola Festa, Meinolf Sellmann, and
Joaquin Vanschoren, 48–59. Lecture Notes in Computer Science. Cham: Springer International
Publishing, 2016. https://doi.org/10.1007/978-3-319-50349-3_4.'
ieee: 'J. Bossek and H. Trautmann, “Evolving Instances for Maximizing Performance
Differences of State-of-the-Art Inexact TSP Solvers,” in Learning and Intelligent
Optimization, 2016, pp. 48–59, doi: 10.1007/978-3-319-50349-3_4.'
mla: Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing Performance
Differences of State-of-the-Art Inexact TSP Solvers.” Learning and Intelligent
Optimization, edited by Paola Festa et al., Springer International Publishing,
2016, pp. 48–59, doi:10.1007/978-3-319-50349-3_4.
short: 'J. Bossek, H. Trautmann, in: P. Festa, M. Sellmann, J. Vanschoren (Eds.),
Learning and Intelligent Optimization, Springer International Publishing, Cham,
2016, pp. 48–59.'
date_created: 2023-11-14T15:58:57Z
date_updated: 2023-12-13T10:47:05Z
department:
- _id: '819'
doi: 10.1007/978-3-319-50349-3_4
editor:
- first_name: Paola
full_name: Festa, Paola
last_name: Festa
- first_name: Meinolf
full_name: Sellmann, Meinolf
last_name: Sellmann
- first_name: Joaquin
full_name: Vanschoren, Joaquin
last_name: Vanschoren
extern: '1'
keyword:
- Algorithm selection
- Feature selection
- Instance hardness
- TSP
language:
- iso: eng
page: 48–59
place: Cham
publication: Learning and Intelligent Optimization
publication_identifier:
isbn:
- 978-3-319-50349-3
publication_status: published
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: Evolving Instances for Maximizing Performance Differences of State-of-the-Art
Inexact TSP Solvers
type: conference
user_id: '102979'
year: '2016'
...
---
_id: '52803'
author:
- first_name: Stefan
full_name: Borgwardt, Stefan
last_name: Borgwardt
- first_name: Theofilos
full_name: Mailis, Theofilos
last_name: Mailis
- first_name: Rafael
full_name: Peñaloza, Rafael
last_name: Peñaloza
- first_name: Anni-Yasmin
full_name: Turhan, Anni-Yasmin
id: '104470'
last_name: Turhan
citation:
ama: Borgwardt S, Mailis T, Peñaloza R, Turhan A-Y. Answering Fuzzy Conjunctive
Queries Over Finitely Valued Fuzzy Ontologies. Journal on Data Semantics.
2016;5(2):55-75. doi:10.1007/s13740-015-0055-y
apa: Borgwardt, S., Mailis, T., Peñaloza, R., & Turhan, A.-Y. (2016). Answering
Fuzzy Conjunctive Queries Over Finitely Valued Fuzzy Ontologies. Journal on
Data Semantics, 5(2), 55–75. https://doi.org/10.1007/s13740-015-0055-y
bibtex: '@article{Borgwardt_Mailis_Peñaloza_Turhan_2016, title={Answering Fuzzy
Conjunctive Queries Over Finitely Valued Fuzzy Ontologies}, volume={5}, DOI={10.1007/s13740-015-0055-y},
number={2}, journal={Journal on Data Semantics}, publisher={Springer Science and
Business Media LLC}, author={Borgwardt, Stefan and Mailis, Theofilos and Peñaloza,
Rafael and Turhan, Anni-Yasmin}, year={2016}, pages={55–75} }'
chicago: 'Borgwardt, Stefan, Theofilos Mailis, Rafael Peñaloza, and Anni-Yasmin
Turhan. “Answering Fuzzy Conjunctive Queries Over Finitely Valued Fuzzy Ontologies.”
Journal on Data Semantics 5, no. 2 (2016): 55–75. https://doi.org/10.1007/s13740-015-0055-y.'
ieee: 'S. Borgwardt, T. Mailis, R. Peñaloza, and A.-Y. Turhan, “Answering Fuzzy
Conjunctive Queries Over Finitely Valued Fuzzy Ontologies,” Journal on Data
Semantics, vol. 5, no. 2, pp. 55–75, 2016, doi: 10.1007/s13740-015-0055-y.'
mla: Borgwardt, Stefan, et al. “Answering Fuzzy Conjunctive Queries Over Finitely
Valued Fuzzy Ontologies.” Journal on Data Semantics, vol. 5, no. 2, Springer
Science and Business Media LLC, 2016, pp. 55–75, doi:10.1007/s13740-015-0055-y.
short: S. Borgwardt, T. Mailis, R. Peñaloza, A.-Y. Turhan, Journal on Data Semantics
5 (2016) 55–75.
date_created: 2024-03-25T09:23:39Z
date_updated: 2024-03-25T13:50:33Z
department:
- _id: '888'
doi: 10.1007/s13740-015-0055-y
intvolume: ' 5'
issue: '2'
keyword:
- Artificial Intelligence
- Computer Networks and Communications
- Information Systems
language:
- iso: eng
page: 55-75
publication: Journal on Data Semantics
publication_identifier:
issn:
- 1861-2032
- 1861-2040
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Answering Fuzzy Conjunctive Queries Over Finitely Valued Fuzzy Ontologies
type: journal_article
user_id: '9503'
volume: 5
year: '2016'
...
---
_id: '47240'
author:
- first_name: Yasemin
full_name: Acar, Yasemin
id: '94636'
last_name: Acar
- first_name: Michael
full_name: Backes, Michael
last_name: Backes
- first_name: Sven
full_name: Bugiel, Sven
last_name: Bugiel
- first_name: Sascha
full_name: Fahl, Sascha
last_name: Fahl
- first_name: Patrick
full_name: McDaniel, Patrick
last_name: McDaniel
- first_name: Matthew
full_name: Smith, Matthew
last_name: Smith
citation:
ama: 'Acar Y, Backes M, Bugiel S, Fahl S, McDaniel P, Smith M. SoK: Lessons Learned
from Android Security Research for Appified Software Platforms. In: 2016 IEEE
Symposium on Security and Privacy (SP). IEEE; 2016. doi:10.1109/sp.2016.33'
apa: 'Acar, Y., Backes, M., Bugiel, S., Fahl, S., McDaniel, P., & Smith, M.
(2016). SoK: Lessons Learned from Android Security Research for Appified Software
Platforms. 2016 IEEE Symposium on Security and Privacy (SP). https://doi.org/10.1109/sp.2016.33'
bibtex: '@inproceedings{Acar_Backes_Bugiel_Fahl_McDaniel_Smith_2016, title={SoK:
Lessons Learned from Android Security Research for Appified Software Platforms},
DOI={10.1109/sp.2016.33}, booktitle={2016
IEEE Symposium on Security and Privacy (SP)}, publisher={IEEE}, author={Acar,
Yasemin and Backes, Michael and Bugiel, Sven and Fahl, Sascha and McDaniel, Patrick
and Smith, Matthew}, year={2016} }'
chicago: 'Acar, Yasemin, Michael Backes, Sven Bugiel, Sascha Fahl, Patrick McDaniel,
and Matthew Smith. “SoK: Lessons Learned from Android Security Research for Appified
Software Platforms.” In 2016 IEEE Symposium on Security and Privacy (SP).
IEEE, 2016. https://doi.org/10.1109/sp.2016.33.'
ieee: 'Y. Acar, M. Backes, S. Bugiel, S. Fahl, P. McDaniel, and M. Smith, “SoK:
Lessons Learned from Android Security Research for Appified Software Platforms,”
2016, doi: 10.1109/sp.2016.33.'
mla: 'Acar, Yasemin, et al. “SoK: Lessons Learned from Android Security Research
for Appified Software Platforms.” 2016 IEEE Symposium on Security and Privacy
(SP), IEEE, 2016, doi:10.1109/sp.2016.33.'
short: 'Y. Acar, M. Backes, S. Bugiel, S. Fahl, P. McDaniel, M. Smith, in: 2016
IEEE Symposium on Security and Privacy (SP), IEEE, 2016.'
date_created: 2023-09-22T12:41:43Z
date_updated: 2024-06-05T13:14:55Z
department:
- _id: '34'
- _id: '858'
doi: 10.1109/sp.2016.33
extern: '1'
language:
- iso: eng
publication: 2016 IEEE Symposium on Security and Privacy (SP)
publication_status: published
publisher: IEEE
status: public
title: 'SoK: Lessons Learned from Android Security Research for Appified Software
Platforms'
type: conference
user_id: '14931'
year: '2016'
...