Viktor Bengs

Fakultät für Elektrotechnik, Informatik und Mathematik
Institut für Informatik
Intelligente Systeme und Maschinelles Lernen
viktor.bengs@uni-paderborn.de
ID
76599

7 Publications

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[7]
2022 | Preprint | LibreCat-ID: 30868
A Survey of Methods for Automated Algorithm Configuration
E. Schede, J. Brandt, A. Tornede, M.D. Wever, V. Bengs, E. Hüllermeier, K. Tierney, ArXiv:2202.01651 (2022).
LibreCat | arXiv
 
[6]
2022 | Preprint | LibreCat-ID: 30867
Machine Learning for Online Algorithm Selection under Censored Feedback
A. Tornede, V. Bengs, E. Hüllermeier, Proceedings of the 36th AAAI Conference on Artificial Intelligence (2022).
LibreCat | arXiv
 
[5]
2020 | Book Chapter | LibreCat-ID: 18014
Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach
A. El Mesaoudi-Paul, D. Weiß, V. Bengs, E. Hüllermeier, K. Tierney, in: Learning and Intelligent Optimization. LION 2020., Springer, Cham, 2020, pp. 216–232.
LibreCat | DOI
 
[4]
2020 | Preprint | LibreCat-ID: 18017
Online Preselection with Context Information under the Plackett-Luce Model
A. El Mesaoudi-Paul, V. Bengs, E. Hüllermeier, ArXiv:2002.04275 (n.d.).
LibreCat
 
[3]
2019 | Journal Article | LibreCat-ID: 14027
Asymptotic confidence sets for the jump curve in bivariate regression problems
V. Bengs, M. Eulert, H. Holzmann, Journal of Multivariate Analysis (2019) 291–312.
LibreCat | DOI
 
[2]
2019 | Journal Article | LibreCat-ID: 14028
Adaptive confidence sets for kink estimation
V. Bengs, H. Holzmann, Electronic Journal of Statistics (2019) 1523–1579.
LibreCat | DOI
 
[1]
2018 | Dissertation | LibreCat-ID: 14031
Confidence sets for change-point problems in nonparametric regression
V. Bengs, Confidence Sets for Change-Point Problems in Nonparametric Regression , 2018.
LibreCat | DOI
 
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7 Publications

Mark all

[7]
2022 | Preprint | LibreCat-ID: 30868
A Survey of Methods for Automated Algorithm Configuration
E. Schede, J. Brandt, A. Tornede, M.D. Wever, V. Bengs, E. Hüllermeier, K. Tierney, ArXiv:2202.01651 (2022).
LibreCat | arXiv
 
[6]
2022 | Preprint | LibreCat-ID: 30867
Machine Learning for Online Algorithm Selection under Censored Feedback
A. Tornede, V. Bengs, E. Hüllermeier, Proceedings of the 36th AAAI Conference on Artificial Intelligence (2022).
LibreCat | arXiv
 
[5]
2020 | Book Chapter | LibreCat-ID: 18014
Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach
A. El Mesaoudi-Paul, D. Weiß, V. Bengs, E. Hüllermeier, K. Tierney, in: Learning and Intelligent Optimization. LION 2020., Springer, Cham, 2020, pp. 216–232.
LibreCat | DOI
 
[4]
2020 | Preprint | LibreCat-ID: 18017
Online Preselection with Context Information under the Plackett-Luce Model
A. El Mesaoudi-Paul, V. Bengs, E. Hüllermeier, ArXiv:2002.04275 (n.d.).
LibreCat
 
[3]
2019 | Journal Article | LibreCat-ID: 14027
Asymptotic confidence sets for the jump curve in bivariate regression problems
V. Bengs, M. Eulert, H. Holzmann, Journal of Multivariate Analysis (2019) 291–312.
LibreCat | DOI
 
[2]
2019 | Journal Article | LibreCat-ID: 14028
Adaptive confidence sets for kink estimation
V. Bengs, H. Holzmann, Electronic Journal of Statistics (2019) 1523–1579.
LibreCat | DOI
 
[1]
2018 | Dissertation | LibreCat-ID: 14031
Confidence sets for change-point problems in nonparametric regression
V. Bengs, Confidence Sets for Change-Point Problems in Nonparametric Regression , 2018.
LibreCat | DOI
 
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