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
Schede E, Brandt J, Tornede A, et al. A Survey of Methods for Automated Algorithm Configuration. arXiv:220201651. Published online 2022.
LibreCat | arXiv
 
[6]
2022 | Preprint | LibreCat-ID: 30867
Tornede A, Bengs V, Hüllermeier E. Machine Learning for Online Algorithm Selection under Censored Feedback. Proceedings of the 36th AAAI Conference on Artificial Intelligence. Published online 2022.
LibreCat | arXiv
 
[5]
2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul A, Weiß D, Bengs V, Hüllermeier E, Tierney K. Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. In: Learning and Intelligent Optimization. LION 2020. Vol 12096. Lecture Notes in Computer Science. Cham: Springer; 2020:216-232. doi:10.1007/978-3-030-53552-0_22
LibreCat | DOI
 
[4]
2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul A, Bengs V, Hüllermeier E. Online Preselection with Context Information under the Plackett-Luce  Model. arXiv:200204275.
LibreCat
 
[3]
2019 | Journal Article | LibreCat-ID: 14027
Bengs V, Eulert M, Holzmann H. Asymptotic confidence sets for the jump curve in bivariate regression problems. Journal of Multivariate Analysis. 2019:291-312. doi:10.1016/j.jmva.2019.02.017
LibreCat | DOI
 
[2]
2019 | Journal Article | LibreCat-ID: 14028
Bengs V, Holzmann H. Adaptive confidence sets for kink estimation. Electronic Journal of Statistics. 2019:1523-1579. doi:10.1214/19-ejs1555
LibreCat | DOI
 
[1]
2018 | Dissertation | LibreCat-ID: 14031
Bengs V. Confidence Sets for Change-Point Problems in Nonparametric Regression .; 2018. doi:https://doi.org/10.17192/z2018.0511
LibreCat | DOI
 
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7 Publications

Mark all

[7]
2022 | Preprint | LibreCat-ID: 30868
Schede E, Brandt J, Tornede A, et al. A Survey of Methods for Automated Algorithm Configuration. arXiv:220201651. Published online 2022.
LibreCat | arXiv
 
[6]
2022 | Preprint | LibreCat-ID: 30867
Tornede A, Bengs V, Hüllermeier E. Machine Learning for Online Algorithm Selection under Censored Feedback. Proceedings of the 36th AAAI Conference on Artificial Intelligence. Published online 2022.
LibreCat | arXiv
 
[5]
2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul A, Weiß D, Bengs V, Hüllermeier E, Tierney K. Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. In: Learning and Intelligent Optimization. LION 2020. Vol 12096. Lecture Notes in Computer Science. Cham: Springer; 2020:216-232. doi:10.1007/978-3-030-53552-0_22
LibreCat | DOI
 
[4]
2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul A, Bengs V, Hüllermeier E. Online Preselection with Context Information under the Plackett-Luce  Model. arXiv:200204275.
LibreCat
 
[3]
2019 | Journal Article | LibreCat-ID: 14027
Bengs V, Eulert M, Holzmann H. Asymptotic confidence sets for the jump curve in bivariate regression problems. Journal of Multivariate Analysis. 2019:291-312. doi:10.1016/j.jmva.2019.02.017
LibreCat | DOI
 
[2]
2019 | Journal Article | LibreCat-ID: 14028
Bengs V, Holzmann H. Adaptive confidence sets for kink estimation. Electronic Journal of Statistics. 2019:1523-1579. doi:10.1214/19-ejs1555
LibreCat | DOI
 
[1]
2018 | Dissertation | LibreCat-ID: 14031
Bengs V. Confidence Sets for Change-Point Problems in Nonparametric Regression .; 2018. doi:https://doi.org/10.17192/z2018.0511
LibreCat | DOI
 
Marked Publication(s)

Search

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Citation Style: AMA

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