---
_id: '10148'
author:
- first_name: Adil
full_name: El Mesaoudi-Paul, Adil
last_name: El Mesaoudi-Paul
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Robert
full_name: Busa-Fekete, Robert
last_name: Busa-Fekete
citation:
ama: 'El Mesaoudi-Paul A, Hüllermeier E, Busa-Fekete R. Ranking Distributions based
on Noisy Sorting. In: Proc. 35th Int. Conference on Machine Learning (ICML).
Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn. Verlagsschriftenreihe
des Heinz Nixdorf Instituts, Paderborn; 2018:3469-3477.'
apa: El Mesaoudi-Paul, A., Hüllermeier, E., & Busa-Fekete, R. (2018). Ranking
Distributions based on Noisy Sorting. Proc. 35th Int. Conference on Machine
Learning (ICML), 3469–3477.
bibtex: '@inproceedings{El Mesaoudi-Paul_Hüllermeier_Busa-Fekete_2018, series={Verlagsschriftenreihe
des Heinz Nixdorf Instituts, Paderborn}, title={Ranking Distributions based on
Noisy Sorting}, booktitle={Proc. 35th Int. Conference on Machine Learning (ICML)},
publisher={Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn}, author={El
Mesaoudi-Paul, Adil and Hüllermeier, Eyke and Busa-Fekete, Robert}, year={2018},
pages={3469–3477}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts,
Paderborn} }'
chicago: El Mesaoudi-Paul, Adil, Eyke Hüllermeier, and Robert Busa-Fekete. “Ranking
Distributions Based on Noisy Sorting.” In Proc. 35th Int. Conference on Machine
Learning (ICML), 3469–77. Verlagsschriftenreihe Des Heinz Nixdorf Instituts,
Paderborn. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
ieee: A. El Mesaoudi-Paul, E. Hüllermeier, and R. Busa-Fekete, “Ranking Distributions
based on Noisy Sorting,” in Proc. 35th Int. Conference on Machine Learning
(ICML), 2018, pp. 3469–3477.
mla: El Mesaoudi-Paul, Adil, et al. “Ranking Distributions Based on Noisy Sorting.”
Proc. 35th Int. Conference on Machine Learning (ICML), Verlagsschriftenreihe
des Heinz Nixdorf Instituts, Paderborn, 2018, pp. 3469–77.
short: 'A. El Mesaoudi-Paul, E. Hüllermeier, R. Busa-Fekete, in: Proc. 35th Int.
Conference on Machine Learning (ICML), Verlagsschriftenreihe des Heinz Nixdorf
Instituts, Paderborn, 2018, pp. 3469–3477.'
date_created: 2019-06-07T09:02:37Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 3469-3477
publication: Proc. 35th Int. Conference on Machine Learning (ICML)
publisher: Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn
series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn
status: public
title: Ranking Distributions based on Noisy Sorting
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10149'
author:
- first_name: M.
full_name: Hesse, M.
last_name: Hesse
- first_name: J.
full_name: Timmermann, J.
last_name: Timmermann
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Ansgar
full_name: Trächtler, Ansgar
last_name: Trächtler
citation:
ama: 'Hesse M, Timmermann J, Hüllermeier E, Trächtler A. A Reinforcement Learning
Strategy for the Swing-Up of the Double Pendulum on a Cart. In: Proc. 4th Int.
Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected
Systems in Products and Production, Procedia Manufacturing 24. ; 2018:15-20.'
apa: 'Hesse, M., Timmermann, J., Hüllermeier, E., & Trächtler, A. (2018). A
Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.
Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible
and Connected Systems in Products and Production, Procedia Manufacturing 24,
15–20.'
bibtex: '@inproceedings{Hesse_Timmermann_Hüllermeier_Trächtler_2018, title={A Reinforcement
Learning Strategy for the Swing-Up of the Double Pendulum on a Cart}, booktitle={Proc.
4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and
Connected Systems in Products and Production, Procedia Manufacturing 24}, author={Hesse,
M. and Timmermann, J. and Hüllermeier, Eyke and Trächtler, Ansgar}, year={2018},
pages={15–20} }'
chicago: 'Hesse, M., J. Timmermann, Eyke Hüllermeier, and Ansgar Trächtler. “A Reinforcement
Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.” In Proc.
4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and
Connected Systems in Products and Production, Procedia Manufacturing 24, 15–20,
2018.'
ieee: 'M. Hesse, J. Timmermann, E. Hüllermeier, and A. Trächtler, “A Reinforcement
Learning Strategy for the Swing-Up of the Double Pendulum on a Cart,” in Proc.
4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and
Connected Systems in Products and Production, Procedia Manufacturing 24, 2018,
pp. 15–20.'
mla: 'Hesse, M., et al. “A Reinforcement Learning Strategy for the Swing-Up of the
Double Pendulum on a Cart.” Proc. 4th Int. Conference on System-Integrated
Intelligence: Intelligent, Flexible and Connected Systems in Products and Production,
Procedia Manufacturing 24, 2018, pp. 15–20.'
short: 'M. Hesse, J. Timmermann, E. Hüllermeier, A. Trächtler, in: Proc. 4th Int.
Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected
Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.'
date_created: 2019-06-07T09:10:51Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 15-20
publication: 'Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent,
Flexible and Connected Systems in Products and Production, Procedia Manufacturing
24'
status: public
title: A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on
a Cart
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10152'
author:
- first_name: E.Loza
full_name: Mencia, E.Loza
last_name: Mencia
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: M.
full_name: Rapp, M.
last_name: Rapp
citation:
ama: 'Mencia EL, Fürnkranz J, Hüllermeier E, Rapp M. Learning interpretable rules
for multi-label classification. In: Jair Escalante H, Escalera S, Guyon I, et
al., eds. Explainable and Interpretable Models in Computer Vision and Machine
Learning. The Springer Series on Challenges in Machine Learning. Springer;
2018:81-113.'
apa: Mencia, E. L., Fürnkranz, J., Hüllermeier, E., & Rapp, M. (2018). Learning
interpretable rules for multi-label classification. In H. Jair Escalante, S. Escalera,
I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, & M. A. J. van Gerven (Eds.),
Explainable and Interpretable Models in Computer Vision and Machine Learning
(pp. 81–113). Springer.
bibtex: '@inbook{Mencia_Fürnkranz_Hüllermeier_Rapp_2018, series={The Springer Series
on Challenges in Machine Learning}, title={Learning interpretable rules for multi-label
classification}, booktitle={Explainable and Interpretable Models in Computer Vision
and Machine Learning}, publisher={Springer}, author={Mencia, E.Loza and Fürnkranz,
J. and Hüllermeier, Eyke and Rapp, M.}, editor={Jair Escalante, H. and Escalera,
S. and Guyon, I. and Baro, X. and Güclüütürk, Y. and Güclü, U. and van Gerven,
M.A.J.Editors}, year={2018}, pages={81–113}, collection={The Springer Series on
Challenges in Machine Learning} }'
chicago: Mencia, E.Loza, J. Fürnkranz, Eyke Hüllermeier, and M. Rapp. “Learning
Interpretable Rules for Multi-Label Classification.” In Explainable and Interpretable
Models in Computer Vision and Machine Learning, edited by H. Jair Escalante,
S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M.A.J. van Gerven,
81–113. The Springer Series on Challenges in Machine Learning. Springer, 2018.
ieee: E. L. Mencia, J. Fürnkranz, E. Hüllermeier, and M. Rapp, “Learning interpretable
rules for multi-label classification,” in Explainable and Interpretable Models
in Computer Vision and Machine Learning, H. Jair Escalante, S. Escalera, I.
Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M. A. J. van Gerven, Eds. Springer,
2018, pp. 81–113.
mla: Mencia, E. Loz., et al. “Learning Interpretable Rules for Multi-Label Classification.”
Explainable and Interpretable Models in Computer Vision and Machine Learning,
edited by H. Jair Escalante et al., Springer, 2018, pp. 81–113.
short: 'E.L. Mencia, J. Fürnkranz, E. Hüllermeier, M. Rapp, in: H. Jair Escalante,
S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, M.A.J. van Gerven (Eds.),
Explainable and Interpretable Models in Computer Vision and Machine Learning,
Springer, 2018, pp. 81–113.'
date_created: 2019-06-07T09:17:56Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
editor:
- first_name: H.
full_name: Jair Escalante, H.
last_name: Jair Escalante
- first_name: S.
full_name: Escalera, S.
last_name: Escalera
- first_name: I.
full_name: Guyon, I.
last_name: Guyon
- first_name: X.
full_name: Baro, X.
last_name: Baro
- first_name: Y.
full_name: Güclüütürk, Y.
last_name: Güclüütürk
- first_name: U.
full_name: Güclü, U.
last_name: Güclü
- first_name: M.A.J.
full_name: van Gerven, M.A.J.
last_name: van Gerven
language:
- iso: eng
page: 81-113
publication: Explainable and Interpretable Models in Computer Vision and Machine Learning
publisher: Springer
series_title: The Springer Series on Challenges in Machine Learning
status: public
title: Learning interpretable rules for multi-label classification
type: book_chapter
user_id: '49109'
year: '2018'
...
---
_id: '10181'
author:
- first_name: Vu-Linh
full_name: Nguyen, Vu-Linh
last_name: Nguyen
- first_name: Sebastian
full_name: Destercke, Sebastian
last_name: Destercke
- first_name: M.-H.
full_name: Masson, M.-H.
last_name: Masson
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Nguyen V-L, Destercke S, Masson M-H, Hüllermeier E. Reliable Multi-class Classification
based on Pairwise Epistemic and Aleatoric Uncertainty. In: Proc. 27th Int.Joint
Conference on Artificial Intelligence (IJCAI). ; 2018:5089-5095.'
apa: Nguyen, V.-L., Destercke, S., Masson, M.-H., & Hüllermeier, E. (2018).
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric
Uncertainty. Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI),
5089–5095.
bibtex: '@inproceedings{Nguyen_Destercke_Masson_Hüllermeier_2018, title={Reliable
Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty},
booktitle={Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI)},
author={Nguyen, Vu-Linh and Destercke, Sebastian and Masson, M.-H. and Hüllermeier,
Eyke}, year={2018}, pages={5089–5095} }'
chicago: Nguyen, Vu-Linh, Sebastian Destercke, M.-H. Masson, and Eyke Hüllermeier.
“Reliable Multi-Class Classification Based on Pairwise Epistemic and Aleatoric
Uncertainty.” In Proc. 27th Int.Joint Conference on Artificial Intelligence
(IJCAI), 5089–95, 2018.
ieee: V.-L. Nguyen, S. Destercke, M.-H. Masson, and E. Hüllermeier, “Reliable Multi-class
Classification based on Pairwise Epistemic and Aleatoric Uncertainty,” in Proc.
27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.
mla: Nguyen, Vu-Linh, et al. “Reliable Multi-Class Classification Based on Pairwise
Epistemic and Aleatoric Uncertainty.” Proc. 27th Int.Joint Conference on Artificial
Intelligence (IJCAI), 2018, pp. 5089–95.
short: 'V.-L. Nguyen, S. Destercke, M.-H. Masson, E. Hüllermeier, in: Proc. 27th
Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.'
date_created: 2019-06-07T12:31:20Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 5089-5095
publication: Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI)
status: public
title: Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric
Uncertainty
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10184'
author:
- first_name: Dirk
full_name: Schäfer, Dirk
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad
Ranking. In: Proc. 21st Int. Conference on Discovery Science (DS). ; 2018:161-175.'
apa: Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement Learning
Using Dyad Ranking. Proc. 21st Int. Conference on Discovery Science (DS),
161–175.
bibtex: '@inproceedings{Schäfer_Hüllermeier_2018, title={Preference-Based Reinforcement
Learning Using Dyad Ranking}, booktitle={Proc. 21st Int. Conference on Discovery
Science (DS)}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={161–175}
}'
chicago: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” In Proc. 21st Int. Conference on Discovery Science (DS),
161–75, 2018.
ieee: D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using
Dyad Ranking,” in Proc. 21st Int. Conference on Discovery Science (DS),
2018, pp. 161–175.
mla: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning
Using Dyad Ranking.” Proc. 21st Int. Conference on Discovery Science (DS),
2018, pp. 161–75.
short: 'D. Schäfer, E. Hüllermeier, in: Proc. 21st Int. Conference on Discovery
Science (DS), 2018, pp. 161–175.'
date_created: 2019-06-07T12:33:58Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
language:
- iso: eng
page: 161-175
publication: Proc. 21st Int. Conference on Discovery Science (DS)
status: public
title: Preference-Based Reinforcement Learning Using Dyad Ranking
type: conference
user_id: '5786'
year: '2018'
...
---
_id: '10276'
author:
- first_name: Dirk
full_name: Schäfer, Dirk
last_name: Schäfer
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Schäfer D, Hüllermeier E. Dyad Ranking Using Plackett-Luce Models based on
joint feature representations. Machine Learning. 2018;107(5):903-941.
apa: Schäfer, D., & Hüllermeier, E. (2018). Dyad Ranking Using Plackett-Luce
Models based on joint feature representations. Machine Learning, 107(5),
903–941.
bibtex: '@article{Schäfer_Hüllermeier_2018, title={Dyad Ranking Using Plackett-Luce
Models based on joint feature representations}, volume={107}, number={5}, journal={Machine
Learning}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={903–941}
}'
chicago: 'Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce
Models Based on Joint Feature Representations.” Machine Learning 107, no.
5 (2018): 903–41.'
ieee: D. Schäfer and E. Hüllermeier, “Dyad Ranking Using Plackett-Luce Models based
on joint feature representations,” Machine Learning, vol. 107, no. 5, pp.
903–941, 2018.
mla: Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models
Based on Joint Feature Representations.” Machine Learning, vol. 107, no.
5, 2018, pp. 903–41.
short: D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941.
date_created: 2019-06-19T14:58:10Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
- _id: '26'
intvolume: ' 107'
issue: '5'
language:
- iso: eng
page: 903-941
publication: Machine Learning
status: public
title: Dyad Ranking Using Plackett-Luce Models based on joint feature representations
type: journal_article
user_id: '49109'
volume: 107
year: '2018'
...
---
_id: '1379'
author:
- first_name: Nina
full_name: Seemann, Nina
id: '65408'
last_name: Seemann
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
- first_name: Marie-Luis
full_name: Merten, Marie-Luis
last_name: Merten
- first_name: Doris
full_name: Tophinke, Doris
id: '16277'
last_name: Tophinke
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Seemann N, Geierhos M, Merten M-L, Tophinke D, Wever MD, Hüllermeier E. Supporting
the Cognitive Process in Annotation Tasks. In: Eckart K, Schlechtweg D, eds. Postersession
Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft.
; 2018.'
apa: Seemann, N., Geierhos, M., Merten, M.-L., Tophinke, D., Wever, M. D., &
Hüllermeier, E. (2018). Supporting the Cognitive Process in Annotation Tasks.
In K. Eckart & D. Schlechtweg (Eds.), Postersession Computerlinguistik
der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft.
bibtex: '@inproceedings{Seemann_Geierhos_Merten_Tophinke_Wever_Hüllermeier_2018,
title={Supporting the Cognitive Process in Annotation Tasks}, booktitle={Postersession
Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft},
author={Seemann, Nina and Geierhos, Michaela and Merten, Marie-Luis and Tophinke,
Doris and Wever, Marcel Dominik and Hüllermeier, Eyke}, editor={Eckart, Kerstin and
Schlechtweg, Dominik }, year={2018} }'
chicago: Seemann, Nina, Michaela Geierhos, Marie-Luis Merten, Doris Tophinke, Marcel
Dominik Wever, and Eyke Hüllermeier. “Supporting the Cognitive Process in Annotation
Tasks.” In Postersession Computerlinguistik der 40. Jahrestagung der Deutschen
Gesellschaft für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg,
2018.
ieee: N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M. D. Wever, and E. Hüllermeier,
“Supporting the Cognitive Process in Annotation Tasks,” in Postersession Computerlinguistik
der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, Stuttgart,
Germany, 2018.
mla: Seemann, Nina, et al. “Supporting the Cognitive Process in Annotation Tasks.”
Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft
für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg,
2018.
short: 'N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M.D. Wever, E. Hüllermeier,
in: K. Eckart, D. Schlechtweg (Eds.), Postersession Computerlinguistik der 40.
Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, 2018.'
conference:
end_date: 2018-03-09
location: Stuttgart, Germany
name: Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft
für Sprachwissenschaft
start_date: 2018-03-07
date_created: 2018-03-19T15:23:25Z
date_updated: 2023-01-09T14:56:56Z
ddc:
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department:
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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
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language:
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main_file_link:
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oa: '1'
project:
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publication: Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft
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quality_controlled: '1'
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title: Supporting the Cognitive Process in Annotation Tasks
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...
---
_id: '24152'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Shalabh
full_name: Bhatnagar, Shalabh
last_name: Bhatnagar
citation:
ama: Ramaswamy A, Bhatnagar S. Analysis of gradient descent methods with nondiminishing
bounded errors. IEEE Transactions on Automatic Control. 2017;63(5):1465-1471.
apa: Ramaswamy, A., & Bhatnagar, S. (2017). Analysis of gradient descent methods
with nondiminishing bounded errors. IEEE Transactions on Automatic Control,
63(5), 1465–1471.
bibtex: '@article{Ramaswamy_Bhatnagar_2017, title={Analysis of gradient descent
methods with nondiminishing bounded errors}, volume={63}, number={5}, journal={IEEE
Transactions on Automatic Control}, publisher={IEEE}, author={Ramaswamy, Arunselvan
and Bhatnagar, Shalabh}, year={2017}, pages={1465–1471} }'
chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent
Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic
Control 63, no. 5 (2017): 1465–71.'
ieee: A. Ramaswamy and S. Bhatnagar, “Analysis of gradient descent methods with
nondiminishing bounded errors,” IEEE Transactions on Automatic Control,
vol. 63, no. 5, pp. 1465–1471, 2017.
mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent
Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic
Control, vol. 63, no. 5, IEEE, 2017, pp. 1465–71.
short: A. Ramaswamy, S. Bhatnagar, IEEE Transactions on Automatic Control 63 (2017)
1465–1471.
date_created: 2021-09-10T10:19:40Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
extern: '1'
intvolume: ' 63'
issue: '5'
language:
- iso: eng
page: 1465-1471
publication: IEEE Transactions on Automatic Control
publisher: IEEE
status: public
title: Analysis of gradient descent methods with nondiminishing bounded errors
type: journal_article
user_id: '66937'
volume: 63
year: '2017'
...
---
_id: '24153'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Shalabh
full_name: Bhatnagar, Shalabh
last_name: Bhatnagar
citation:
ama: Ramaswamy A, Bhatnagar S. A generalization of the Borkar-Meyn theorem for stochastic
recursive inclusions. Mathematics of Operations Research. 2017;42(3):648-661.
apa: Ramaswamy, A., & Bhatnagar, S. (2017). A generalization of the Borkar-Meyn
theorem for stochastic recursive inclusions. Mathematics of Operations Research,
42(3), 648–661.
bibtex: '@article{Ramaswamy_Bhatnagar_2017, title={A generalization of the Borkar-Meyn
theorem for stochastic recursive inclusions}, volume={42}, number={3}, journal={Mathematics
of Operations Research}, publisher={INFORMS}, author={Ramaswamy, Arunselvan and
Bhatnagar, Shalabh}, year={2017}, pages={648–661} }'
chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the
Borkar-Meyn Theorem for Stochastic Recursive Inclusions.” Mathematics of Operations
Research 42, no. 3 (2017): 648–61.'
ieee: A. Ramaswamy and S. Bhatnagar, “A generalization of the Borkar-Meyn theorem
for stochastic recursive inclusions,” Mathematics of Operations Research,
vol. 42, no. 3, pp. 648–661, 2017.
mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the Borkar-Meyn
Theorem for Stochastic Recursive Inclusions.” Mathematics of Operations Research,
vol. 42, no. 3, INFORMS, 2017, pp. 648–61.
short: A. Ramaswamy, S. Bhatnagar, Mathematics of Operations Research 42 (2017)
648–661.
date_created: 2021-09-10T10:21:02Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
extern: '1'
intvolume: ' 42'
issue: '3'
language:
- iso: eng
page: 648-661
publication: Mathematics of Operations Research
publisher: INFORMS
status: public
title: A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions
type: journal_article
user_id: '66937'
volume: 42
year: '2017'
...
---
_id: '3325'
author:
- first_name: Vitalik
full_name: Melnikov, Vitalik
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics. In: Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing;
2017. doi:10.5445/KSP/1000074341'
apa: 'Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics. In Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing.
https://doi.org/10.5445/KSP/1000074341'
bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure
of Nested Dichotomies: A Comparison of Two Heuristics}, DOI={10.5445/KSP/1000074341},
booktitle={Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23.
- 24. November 2017}, publisher={KIT Scientific Publishing}, author={Melnikov,
Vitalik and Hüllermeier, Eyke}, year={2017} }'
chicago: 'Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of
Nested Dichotomies: A Comparison of Two Heuristics.” In Proceedings. 27. Workshop
Computational Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific
Publishing, 2017. https://doi.org/10.5445/KSP/1000074341.'
ieee: 'V. Melnikov and E. Hüllermeier, “Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics,” in Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017, 2017.'
mla: 'Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics.” Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing,
2017, doi:10.5445/KSP/1000074341.'
short: 'V. Melnikov, E. Hüllermeier, in: Proceedings. 27. Workshop Computational
Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017.'
date_created: 2018-06-25T08:14:49Z
date_updated: 2022-01-06T06:59:10Z
ddc:
- '000'
department:
- _id: '355'
doi: 10.5445/KSP/1000074341
file:
- access_level: closed
content_type: application/pdf
creator: melnikov
date_created: 2018-11-30T09:47:59Z
date_updated: 2018-11-30T09:47:59Z
file_id: '5987'
file_name: main.pdf
file_size: 1829552
relation: main_file
success: 1
file_date_updated: 2018-11-30T09:47:59Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '3'
name: SFB 901 - Project Area B
- _id: '1'
name: SFB 901
publication: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. -
24. November 2017
publisher: KIT Scientific Publishing
status: public
title: 'Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics'
type: conference
user_id: '15504'
year: '2017'
...
---
_id: '115'
abstract:
- lang: eng
text: 'Whenever customers have to decide between different instances of the same
product, they are interested in buying the best product. In contrast, companies
are interested in reducing the construction effort (and usually as a consequence
thereof, the quality) to gain profit. The described setting is widely known as
opposed preferences in quality of the product and also applies to the context
of service-oriented computing. In general, service-oriented computing emphasizes
the construction of large software systems out of existing services, where services
are small and self-contained pieces of software that adhere to a specified interface.
Several implementations of the same interface are considered as several instances
of the same service. Thereby, customers are interested in buying the best service
implementation for their service composition wrt. to metrics, such as costs, energy,
memory consumption, or execution time. One way to ensure the service quality is
to employ certificates, which can come in different kinds: Technical certificates
proving correctness can be automatically constructed by the service provider and
again be automatically checked by the user. Digital certificates allow proof of
the integrity of a product. Other certificates might be rolled out if service
providers follow a good software construction principle, which is checked in annual
audits. Whereas all of these certificates are handled differently in service markets,
what they have in common is that they influence the buying decisions of customers.
In this paper, we review state-of-the-art developments in certification with respect
to service-oriented computing. We not only discuss how certificates are constructed
and handled in service-oriented computing but also review the effects of certificates
on the market from an economic perspective.'
author:
- first_name: Marie-Christine
full_name: Jakobs, Marie-Christine
last_name: Jakobs
- first_name: Julia
full_name: Krämer, Julia
last_name: Krämer
- first_name: Dirk
full_name: van Straaten, Dirk
id: '10311'
last_name: van Straaten
- first_name: Theodor
full_name: Lettmann, Theodor
id: '315'
last_name: Lettmann
orcid: 0000-0001-5859-2457
citation:
ama: 'Jakobs M-C, Krämer J, van Straaten D, Lettmann T. Certification Matters for
Service Markets. In: Marcelo De Barros, Janusz Klink,Tadeus Uhl TP, ed. The
Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION).
; 2017:7-12.'
apa: Jakobs, M.-C., Krämer, J., van Straaten, D., & Lettmann, T. (2017). Certification
Matters for Service Markets. In T. P. Marcelo De Barros, Janusz Klink,Tadeus Uhl
(Ed.), The Ninth International Conferences on Advanced Service Computing (SERVICE
COMPUTATION) (pp. 7–12).
bibtex: '@inproceedings{Jakobs_Krämer_van Straaten_Lettmann_2017, title={Certification
Matters for Service Markets}, booktitle={The Ninth International Conferences on
Advanced Service Computing (SERVICE COMPUTATION)}, author={Jakobs, Marie-Christine
and Krämer, Julia and van Straaten, Dirk and Lettmann, Theodor}, editor={Marcelo
De Barros, Janusz Klink,Tadeus Uhl, Thomas PrinzEditor}, year={2017}, pages={7–12}
}'
chicago: Jakobs, Marie-Christine, Julia Krämer, Dirk van Straaten, and Theodor Lettmann.
“Certification Matters for Service Markets.” In The Ninth International Conferences
on Advanced Service Computing (SERVICE COMPUTATION), edited by Thomas Prinz
Marcelo De Barros, Janusz Klink,Tadeus Uhl, 7–12, 2017.
ieee: M.-C. Jakobs, J. Krämer, D. van Straaten, and T. Lettmann, “Certification Matters
for Service Markets,” in The Ninth International Conferences on Advanced Service
Computing (SERVICE COMPUTATION), 2017, pp. 7–12.
mla: Jakobs, Marie-Christine, et al. “Certification Matters for Service Markets.”
The Ninth International Conferences on Advanced Service Computing (SERVICE
COMPUTATION), edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus
Uhl, 2017, pp. 7–12.
short: 'M.-C. Jakobs, J. Krämer, D. van Straaten, T. Lettmann, in: T.P. Marcelo
De Barros, Janusz Klink,Tadeus Uhl (Ed.), The Ninth International Conferences
on Advanced Service Computing (SERVICE COMPUTATION), 2017, pp. 7–12.'
date_created: 2017-10-17T12:41:14Z
date_updated: 2022-01-06T06:51:02Z
ddc:
- '040'
department:
- _id: '77'
- _id: '355'
- _id: '179'
editor:
- first_name: Thomas Prinz
full_name: Marcelo De Barros, Janusz Klink,Tadeus Uhl, Thomas Prinz
last_name: Marcelo De Barros, Janusz Klink,Tadeus Uhl
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T13:04:12Z
date_updated: 2018-03-21T13:04:12Z
file_id: '1564'
file_name: 115-JakobsKraemerVanStraatenLettmann2017.pdf
file_size: 133531
relation: main_file
success: 1
file_date_updated: 2018-03-21T13:04:12Z
has_accepted_license: '1'
language:
- iso: eng
page: 7-12
project:
- _id: '1'
name: SFB 901
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '12'
name: SFB 901 - Subproject B4
- _id: '8'
name: SFB 901 - Subproject A4
- _id: '2'
name: SFB 901 - Project Area A
- _id: '3'
name: SFB 901 - Project Area B
publication: The Ninth International Conferences on Advanced Service Computing (SERVICE
COMPUTATION)
status: public
title: Certification Matters for Service Markets
type: conference
user_id: '477'
year: '2017'
...
---
_id: '1158'
abstract:
- lang: eng
text: In this paper, we present the annotation challenges we have encountered when
working on a historical language that was undergoing elaboration processes. We
especially focus on syntactic ambiguity and gradience in Middle Low German, which
causes uncertainty to some extent. Since current annotation tools consider construction
contexts and the dynamics of the grammaticalization only partially, we plan to
extend CorA – a web-based annotation tool for historical and other non-standard
language data – to capture elaboration phenomena and annotator unsureness. Moreover,
we seek to interactively learn morphological as well as syntactic annotations.
author:
- first_name: Nina
full_name: Seemann, Nina
id: '65408'
last_name: Seemann
- first_name: Marie-Luis
full_name: Merten, Marie-Luis
last_name: Merten
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
- first_name: Doris
full_name: Tophinke, Doris
last_name: Tophinke
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
citation:
ama: 'Seemann N, Merten M-L, Geierhos M, Tophinke D, Hüllermeier E. Annotation Challenges
for Reconstructing the Structural Elaboration of Middle Low German. In: Proceedings
of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage,
Social Sciences, Humanities and Literature. Stroudsburg, PA, USA: Association
for Computational Linguistics (ACL); 2017:40-45. doi:10.18653/v1/W17-2206'
apa: 'Seemann, N., Merten, M.-L., Geierhos, M., Tophinke, D., & Hüllermeier,
E. (2017). Annotation Challenges for Reconstructing the Structural Elaboration
of Middle Low German. In Proceedings of the Joint SIGHUM Workshop on Computational
Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
(pp. 40–45). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL).
https://doi.org/10.18653/v1/W17-2206'
bibtex: '@inproceedings{Seemann_Merten_Geierhos_Tophinke_Hüllermeier_2017, place={Stroudsburg,
PA, USA}, title={Annotation Challenges for Reconstructing the Structural Elaboration
of Middle Low German}, DOI={10.18653/v1/W17-2206},
booktitle={Proceedings of the Joint SIGHUM Workshop on Computational Linguistics
for Cultural Heritage, Social Sciences, Humanities and Literature}, publisher={Association
for Computational Linguistics (ACL)}, author={Seemann, Nina and Merten, Marie-Luis
and Geierhos, Michaela and Tophinke, Doris and Hüllermeier, Eyke}, year={2017},
pages={40–45} }'
chicago: 'Seemann, Nina, Marie-Luis Merten, Michaela Geierhos, Doris Tophinke, and
Eyke Hüllermeier. “Annotation Challenges for Reconstructing the Structural Elaboration
of Middle Low German.” In Proceedings of the Joint SIGHUM Workshop on Computational
Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature,
40–45. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL),
2017. https://doi.org/10.18653/v1/W17-2206.'
ieee: N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, and E. Hüllermeier, “Annotation
Challenges for Reconstructing the Structural Elaboration of Middle Low German,”
in Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for
Cultural Heritage, Social Sciences, Humanities and Literature, Vancouver,
BC, Canada, 2017, pp. 40–45.
mla: Seemann, Nina, et al. “Annotation Challenges for Reconstructing the Structural
Elaboration of Middle Low German.” Proceedings of the Joint SIGHUM Workshop
on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities
and Literature, Association for Computational Linguistics (ACL), 2017, pp.
40–45, doi:10.18653/v1/W17-2206.
short: 'N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, E. Hüllermeier, in:
Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural
Heritage, Social Sciences, Humanities and Literature, Association for Computational
Linguistics (ACL), Stroudsburg, PA, USA, 2017, pp. 40–45.'
conference:
end_date: 2017-08-04
location: Vancouver, BC, Canada
name: Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage,
Social Sciences, Humanities and Literature (LaTeCH-CLfL 2017)
start_date: 2017-07-31
date_created: 2018-01-31T15:32:33Z
date_updated: 2022-01-06T06:51:03Z
department:
- _id: '36'
- _id: '579'
- _id: '115'
- _id: '355'
- _id: '615'
doi: 10.18653/v1/W17-2206
language:
- iso: eng
page: 40-45
place: Stroudsburg, PA, USA
project:
- _id: '39'
name: InterGramm
publication: Proceedings of the Joint SIGHUM Workshop on Computational Linguistics
for Cultural Heritage, Social Sciences, Humanities and Literature
publication_status: published
publisher: Association for Computational Linguistics (ACL)
quality_controlled: '1'
status: public
title: Annotation Challenges for Reconstructing the Structural Elaboration of Middle
Low German
type: conference
user_id: '13929'
year: '2017'
...
---
_id: '5694'
author:
- first_name: Nino Noel
full_name: Schnitker, Nino Noel
last_name: Schnitker
citation:
ama: Schnitker NN. Genetischer Algorithmus zur Erstellung von Ensembles von Nested
Dichotomies. Universität Paderborn; 2017.
apa: Schnitker, N. N. (2017). Genetischer Algorithmus zur Erstellung von Ensembles
von Nested Dichotomies. Universität Paderborn.
bibtex: '@book{Schnitker_2017, title={Genetischer Algorithmus zur Erstellung von
Ensembles von Nested Dichotomies}, publisher={Universität Paderborn}, author={Schnitker,
Nino Noel}, year={2017} }'
chicago: Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles
von Nested Dichotomies. Universität Paderborn, 2017.
ieee: N. N. Schnitker, Genetischer Algorithmus zur Erstellung von Ensembles von
Nested Dichotomies. Universität Paderborn, 2017.
mla: Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles
von Nested Dichotomies. Universität Paderborn, 2017.
short: N.N. Schnitker, Genetischer Algorithmus zur Erstellung von Ensembles von
Nested Dichotomies, Universität Paderborn, 2017.
date_created: 2018-11-15T08:10:48Z
date_updated: 2022-01-06T07:02:35Z
department:
- _id: '355'
language:
- iso: ger
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
title: Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies
type: bachelorsthesis
user_id: '477'
year: '2017'
...
---
_id: '5722'
author:
- first_name: Pritha
full_name: Gupta, Pritha
last_name: Gupta
- first_name: Alexander
full_name: Hetzer, Alexander
id: '38209'
last_name: Hetzer
- first_name: Tanja
full_name: Tornede, Tanja
last_name: Tornede
- first_name: Sebastian
full_name: Gottschalk, Sebastian
last_name: Gottschalk
- first_name: Andreas
full_name: Kornelsen, Andreas
last_name: Kornelsen
- first_name: Sebastian
full_name: Osterbrink, Sebastian
last_name: Osterbrink
- first_name: Karlson
full_name: Pfannschmidt, Karlson
last_name: Pfannschmidt
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
citation:
ama: 'Gupta P, Hetzer A, Tornede T, et al. jPL: A Java-based Software Framework
for Preference Learning. In: ; 2017.'
apa: 'Gupta, P., Hetzer, A., Tornede, T., Gottschalk, S., Kornelsen, A., Osterbrink,
S., … Hüllermeier, E. (2017). jPL: A Java-based Software Framework for Preference
Learning. Presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock.'
bibtex: '@inproceedings{Gupta_Hetzer_Tornede_Gottschalk_Kornelsen_Osterbrink_Pfannschmidt_Hüllermeier_2017,
title={jPL: A Java-based Software Framework for Preference Learning}, author={Gupta,
Pritha and Hetzer, Alexander and Tornede, Tanja and Gottschalk, Sebastian and
Kornelsen, Andreas and Osterbrink, Sebastian and Pfannschmidt, Karlson and Hüllermeier,
Eyke}, year={2017} }'
chicago: 'Gupta, Pritha, Alexander Hetzer, Tanja Tornede, Sebastian Gottschalk,
Andreas Kornelsen, Sebastian Osterbrink, Karlson Pfannschmidt, and Eyke Hüllermeier.
“JPL: A Java-Based Software Framework for Preference Learning,” 2017.'
ieee: 'P. Gupta et al., “jPL: A Java-based Software Framework for Preference
Learning,” presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock,
2017.'
mla: 'Gupta, Pritha, et al. JPL: A Java-Based Software Framework for Preference
Learning. 2017.'
short: 'P. Gupta, A. Hetzer, T. Tornede, S. Gottschalk, A. Kornelsen, S. Osterbrink,
K. Pfannschmidt, E. Hüllermeier, in: 2017.'
conference:
end_date: 13.09.2017
location: Rostock
name: 'WDA 2017 Workshops: KDML, FGWM, IR, and FGDB'
start_date: 11.09.2017
date_created: 2018-11-19T07:32:31Z
date_updated: 2022-01-06T07:02:37Z
department:
- _id: '355'
extern: '1'
language:
- iso: eng
status: public
title: 'jPL: A Java-based Software Framework for Preference Learning'
type: conference_abstract
user_id: '38209'
year: '2017'
...
---
_id: '5724'
author:
- first_name: Alexander
full_name: Hetzer, Alexander
id: '38209'
last_name: Hetzer
- first_name: Tanja
full_name: Tornede, Tanja
last_name: Tornede
citation:
ama: Hetzer A, Tornede T. Solving the Container Pre-Marshalling Problem Using
Reinforcement Learning and Structured Output Prediction. Universität Paderborn;
2017.
apa: Hetzer, A., & Tornede, T. (2017). Solving the Container Pre-Marshalling
Problem using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn.
bibtex: '@book{Hetzer_Tornede_2017, title={Solving the Container Pre-Marshalling
Problem using Reinforcement Learning and Structured Output Prediction}, publisher={Universität
Paderborn}, author={Hetzer, Alexander and Tornede, Tanja}, year={2017} }'
chicago: Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling
Problem Using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn, 2017.
ieee: A. Hetzer and T. Tornede, Solving the Container Pre-Marshalling Problem
using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn, 2017.
mla: Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling
Problem Using Reinforcement Learning and Structured Output Prediction. Universität
Paderborn, 2017.
short: A. Hetzer, T. Tornede, Solving the Container Pre-Marshalling Problem Using
Reinforcement Learning and Structured Output Prediction, Universität Paderborn,
2017.
date_created: 2018-11-19T07:49:13Z
date_updated: 2022-01-06T07:02:37Z
department:
- _id: '355'
- _id: '199'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Kevin
full_name: Tierney, Kevin
last_name: Tierney
title: Solving the Container Pre-Marshalling Problem using Reinforcement Learning
and Structured Output Prediction
type: mastersthesis
user_id: '477'
year: '2017'
...
---
_id: '71'
abstract:
- lang: eng
text: Today, software verification tools have reached the maturity to be used for
large scale programs. Different tools perform differently well on varying code.
A software developer is hence faced with the problem of choosing a tool appropriate
for her program at hand. A ranking of tools on programs could facilitate the choice.
Such rankings can, however, so far only be obtained by running all considered
tools on the program.In this paper, we present a machine learning approach to
predicting rankings of tools on programs. The method builds upon so-called label
ranking algorithms, which we complement with appropriate kernels providing a similarity
measure for programs. Our kernels employ a graph representation for software source
code that mixes elements of control flow and program dependence graphs with abstract
syntax trees. Using data sets from the software verification competition SV-COMP,
we demonstrate our rank prediction technique to generalize well and achieve a
rather high predictive accuracy (rank correlation > 0.6).
author:
- first_name: Mike
full_name: Czech, Mike
last_name: Czech
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Marie-Christine
full_name: Jakobs, Marie-Christine
last_name: Jakobs
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: 'Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software
Verification Tools. In: Proceedings of the 3rd International Workshop on Software
Analytics. SWAN’17. ; 2017:23-26. doi:10.1145/3121257.3121262'
apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting
Rankings of Software Verification Tools. In Proceedings of the 3rd International
Workshop on Software Analytics (pp. 23–26). https://doi.org/10.1145/3121257.3121262
bibtex: '@inproceedings{Czech_Hüllermeier_Jakobs_Wehrheim_2017, series={SWAN’17},
title={Predicting Rankings of Software Verification Tools}, DOI={10.1145/3121257.3121262},
booktitle={Proceedings of the 3rd International Workshop on Software Analytics},
author={Czech, Mike and Hüllermeier, Eyke and Jakobs, Marie-Christine and Wehrheim,
Heike}, year={2017}, pages={23–26}, collection={SWAN’17} }'
chicago: Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim.
“Predicting Rankings of Software Verification Tools.” In Proceedings of the
3rd International Workshop on Software Analytics, 23–26. SWAN’17, 2017. https://doi.org/10.1145/3121257.3121262.
ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, “Predicting Rankings
of Software Verification Tools,” in Proceedings of the 3rd International Workshop
on Software Analytics, 2017, pp. 23–26.
mla: Czech, Mike, et al. “Predicting Rankings of Software Verification Tools.” Proceedings
of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26,
doi:10.1145/3121257.3121262.
short: 'M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proceedings of
the 3rd International Workshop on Software Analytics, 2017, pp. 23–26.'
date_created: 2017-10-17T12:41:05Z
date_updated: 2022-01-06T07:03:28Z
ddc:
- '000'
department:
- _id: '355'
- _id: '77'
doi: 10.1145/3121257.3121262
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T14:24:29Z
date_updated: 2018-11-02T14:24:29Z
file_id: '5271'
file_name: fsews17swan-swanmain1.pdf
file_size: 822383
relation: main_file
success: 1
file_date_updated: 2018-11-02T14:24:29Z
has_accepted_license: '1'
language:
- iso: eng
page: 23-26
project:
- _id: '1'
name: SFB 901
- _id: '12'
name: SFB 901 - Subprojekt B4
- _id: '10'
name: SFB 901 - Subproject B2
- _id: '3'
name: SFB 901 - Project Area B
- _id: '11'
name: SFB 901 - Subproject B3
publication: Proceedings of the 3rd International Workshop on Software Analytics
series_title: SWAN'17
status: public
title: Predicting Rankings of Software Verification Tools
type: conference
user_id: '15504'
year: '2017'
...
---
_id: '72'
abstract:
- lang: eng
text: 'Software verification competitions, such as the annual SV-COMP, evaluate
software verification tools with respect to their effectivity and efficiency.
Typically, the outcome of a competition is a (possibly category-specific) ranking
of the tools. For many applications, such as building portfolio solvers, it would
be desirable to have an idea of the (relative) performance of verification tools
on a given verification task beforehand, i.e., prior to actually running all tools
on the task.In this paper, we present a machine learning approach to predicting
rankings of tools on verification tasks. The method builds upon so-called label
ranking algorithms, which we complement with appropriate kernels providing a similarity
measure for verification tasks. Our kernels employ a graph representation for
software source code that mixes elements of control flow and program dependence
graphs with abstract syntax trees. Using data sets from SV-COMP, we demonstrate
our rank prediction technique to generalize well and achieve a rather high predictive
accuracy. In particular, our method outperforms a recently proposed feature-based
approach of Demyanova et al. (when applied to rank predictions). '
author:
- first_name: Mike
full_name: Czech, Mike
last_name: Czech
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Marie-Christine
full_name: Jakobs, Marie-Christine
last_name: Jakobs
- first_name: Heike
full_name: Wehrheim, Heike
id: '573'
last_name: Wehrheim
citation:
ama: Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software
Verification Competitions.; 2017.
apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting
Rankings of Software Verification Competitions.
bibtex: '@book{Czech_Hüllermeier_Jakobs_Wehrheim_2017, title={Predicting Rankings
of Software Verification Competitions}, author={Czech, Mike and Hüllermeier, Eyke
and Jakobs, Marie-Christine and Wehrheim, Heike}, year={2017} }'
chicago: Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim.
Predicting Rankings of Software Verification Competitions, 2017.
ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, Predicting Rankings
of Software Verification Competitions. 2017.
mla: Czech, Mike, et al. Predicting Rankings of Software Verification Competitions.
2017.
short: M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Predicting Rankings
of Software Verification Competitions, 2017.
date_created: 2017-10-17T12:41:05Z
date_updated: 2022-01-06T07:03:29Z
ddc:
- '000'
department:
- _id: '77'
- _id: '355'
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-11-21T10:50:11Z
date_updated: 2018-11-21T10:50:11Z
file_id: '5782'
file_name: "Predicting Rankings of So\x81ware Verification Competitions.pdf"
file_size: 869984
relation: main_file
success: 1
file_date_updated: 2018-11-21T10:50:11Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '11'
name: SFB 901 - Subprojekt B3
- _id: '12'
name: SFB 901 - Subprojekt B4
- _id: '3'
name: SFB 901 - Project Area B
status: public
title: Predicting Rankings of Software Verification Competitions
type: report
user_id: '15504'
year: '2017'
...
---
_id: '10589'
author:
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Encyclopedia of Machine
Learning and Data Mining. ; 2017:1000-1005.'
apa: Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In Encyclopedia
of Machine Learning and Data Mining (pp. 1000–1005).
bibtex: '@inbook{Fürnkranz_Hüllermeier_2017, title={Preference Learning}, booktitle={Encyclopedia
of Machine Learning and Data Mining}, author={Fürnkranz, J. and Hüllermeier, Eyke},
year={2017}, pages={1000–1005} }'
chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia
of Machine Learning and Data Mining, 1000–1005, 2017.
ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia
of Machine Learning and Data Mining, 2017, pp. 1000–1005.
mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia
of Machine Learning and Data Mining, 2017, pp. 1000–05.
short: 'J. Fürnkranz, E. Hüllermeier, in: Encyclopedia of Machine Learning and Data
Mining, 2017, pp. 1000–1005.'
date_created: 2019-07-09T15:37:09Z
date_updated: 2022-01-06T06:50:45Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 1000-1005
publication: Encyclopedia of Machine Learning and Data Mining
status: public
title: Preference Learning
type: encyclopedia_article
user_id: '49109'
year: '2017'
...
---
_id: '10784'
author:
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds.
Encyclopedia of Machine Learning and Data Mining. Vol 107. Springer; 2017:1000-1005.'
apa: Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In C. Sammut
& G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining
(Vol. 107, pp. 1000–1005). Springer.
bibtex: '@inbook{Fürnkranz_Hüllermeier_2017, title={Preference Learning}, volume={107},
booktitle={Encyclopedia of Machine Learning and Data Mining}, publisher={Springer},
author={Fürnkranz, J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors},
year={2017}, pages={1000–1005} }'
chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, 107:1000–1005.
Springer, 2017.
ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia
of Machine Learning and Data Mining, vol. 107, C. Sammut and G. I. Webb, Eds.
Springer, 2017, pp. 1000–1005.
mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, vol.
107, Springer, 2017, pp. 1000–05.
short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia
of Machine Learning and Data Mining, Springer, 2017, pp. 1000–1005.'
date_created: 2019-07-10T15:44:32Z
date_updated: 2022-01-06T06:50:50Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
editor:
- first_name: C.
full_name: Sammut, C.
last_name: Sammut
- first_name: G.I.
full_name: Webb, G.I.
last_name: Webb
intvolume: ' 107'
language:
- iso: eng
page: 1000-1005
publication: Encyclopedia of Machine Learning and Data Mining
publisher: Springer
status: public
title: Preference Learning
type: book_chapter
user_id: '49109'
volume: 107
year: '2017'
...
---
_id: '1180'
abstract:
- lang: eng
text: These days, there is a strong rise in the needs for machine learning applications,
requiring an automation of machine learning engineering which is referred to as
AutoML. In AutoML the selection, composition and parametrization of machine learning
algorithms is automated and tailored to a specific problem, resulting in a machine
learning pipeline. Current approaches reduce the AutoML problem to optimization
of hyperparameters. Based on recursive task networks, in this paper we present
one approach from the field of automated planning and one evolutionary optimization
approach. Instead of simply parametrizing a given pipeline, this allows for structure
optimization of machine learning pipelines, as well. We evaluate the two approaches
in an extensive evaluation, finding both approaches to have their strengths in
different areas. Moreover, the two approaches outperform the state-of-the-art
tool Auto-WEKA in many settings.
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierachical Planning
Versus Evolutionary Optimization. In: 27th Workshop Computational Intelligence.
Dortmund; 2017.'
apa: 'Wever, M. D., Mohr, F., & Hüllermeier, E. (2017). Automatic Machine Learning:
Hierachical Planning Versus Evolutionary Optimization. In 27th Workshop Computational
Intelligence. Dortmund.'
bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2017, place={Dortmund}, title={Automatic
Machine Learning: Hierachical Planning Versus Evolutionary Optimization}, booktitle={27th
Workshop Computational Intelligence}, author={Wever, Marcel Dominik and Mohr,
Felix and Hüllermeier, Eyke}, year={2017} }'
chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automatic Machine
Learning: Hierachical Planning Versus Evolutionary Optimization.” In 27th Workshop
Computational Intelligence. Dortmund, 2017.'
ieee: 'M. D. Wever, F. Mohr, and E. Hüllermeier, “Automatic Machine Learning: Hierachical
Planning Versus Evolutionary Optimization,” in 27th Workshop Computational
Intelligence, Dortmund, 2017.'
mla: 'Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning
Versus Evolutionary Optimization.” 27th Workshop Computational Intelligence,
2017.'
short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence,
Dortmund, 2017.'
conference:
end_date: 2017-11-24
location: Dortmund
name: 27th Workshop Computational Intelligence
start_date: 2017-11-23
date_created: 2018-02-22T07:19:18Z
date_updated: 2022-01-06T06:51:09Z
ddc:
- '000'
department:
- _id: '355'
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:28:09Z
date_updated: 2018-11-06T15:28:09Z
file_id: '5387'
file_name: CI Workshop AutoML.pdf
file_size: 323589
relation: main_file
success: 1
file_date_updated: 2018-11-06T15:28:09Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://publikationen.bibliothek.kit.edu/1000074341/4643874
oa: '1'
place: Dortmund
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: 27th Workshop Computational Intelligence
publication_status: published
status: public
title: 'Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization'
type: conference
user_id: '49109'
year: '2017'
...