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Gruppiert nach: Dokumententyp | Veröffentlichungsdatum
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Anzahl der Publikationen: 30

Hochschulschrift

Bengs, Viktor (2018): Confidence sets for change-point problems in nonparametric regression. Dissertation, Philipps-Universität Marburg

Zeitschriftenartikel

Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186 und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (16. November 2022): Multi-armed bandits with censored consumption of resources. In: Machine Learning, Bd. 112, Nr. 2: S. 217-240 [PDF, 2MB]

Schede, Elias; Brandt, Jasmin; Tornede, Alexander ORCID logoORCID: https://orcid.org/0000-0002-2415-2186; Wever, Marcel ORCID logoORCID: https://orcid.org/0000-0001-9782-6818; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Tierney, Kevin (Oktober 2022): A Survey of Methods for Automated Algorithm Configuration. In: Journal of Artificial Intelligence Research, Bd. 75: S. 425-487 [PDF, 852kB]

Schede, Elias; Brandt, Jasmin; Tornede, Alexander; Wever, Marcel; Bengs, Viktor; Huellermeier, Eyke und Tierney, Kevin (2022): A Survey of Methods for Automated Algorithm Configuration. In: Journal of Artificial Intelligence Research, Bd. 75: S. 425-487

Haddenhorst, Björn ORCID logoORCID: https://orcid.org/0000-0002-4023-6646; Bengs, Viktor und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Juli 2021): On testing transitivity in online preference learning. In: Machine Learning, Bd. 110, Nr. 8: S. 2063-2084 [PDF, 2MB]

Bengs, Viktor; Busa-Fekete, Róbert; Mesaoudi-Paul, Adil El und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Januar 2021): Preference-based Online Learning with Dueling Bandits: A Survey. In: Journal of Machine Learning Research, Bd. 22, Nr. 7: S. 1-108 [PDF, 918kB]

Haddenhorst, Björn; Bengs, Viktor und Hüllermeier, Eyke (2021): On testing transitivity in online preference learning. In: Machine Learning, Bd. 110, Nr. 8: S. 2063-2084

Bengs, Viktor und Holzmann, Hajo (2019): Adaptive confidence sets for kink estimation. In: Electronic Journal of Statistics, Bd. 13, Nr. 1: S. 1523-1579 [PDF, 726kB]

Bengs, Viktor; Eulert, Matthias und Holzmann, Hajo (2019): Asymptotic confidence sets for the jump curve in bivariate regression problems. In: Journal of Multivariate Analysis, Bd. 173: S. 291-312

Buchbeitrag

El Mesaoudi-Paul, Adil; Weiß, Dimitri; Bengs, Viktor; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Tierney, Kevin (Mai 2020): Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. In: Kotsireas, Ilias S. und Pardalos, Panos M. (Hrsg.): Learning and Intelligent Optimization. 14th International Conference, LION 14, Athens, Greece, May 24–28, 2020, Revised Selected Papers. Lecture Notes in Computer Science, Bd. 12096. Cham: Springer. S. 216-232

Konferenzbeitrag

Brandt, Jasmin; Wever, Marcel ORCID logoORCID: https://orcid.org/0000-0001-9782-6818; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186 und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (August 2024): Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO. Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24), Jeju, South Korea, 3. - 9. August 2024. Larson, Kate (Hrsg.): In: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization. S. 3742-3750

Sale, Yusuf; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Caprio, Michele und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Juli 2024): Second-Order Uncertainty Quantification: A Distance-Based Approach. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 21. - 27. July 2024. In: Proceedings of the 41st International Conference on Machine Learning, Proceedings of Machine Learning Research Bd. 235 PMLR. S. 43060-43076 [PDF, 2MB]

Juergens, Mira; Meinert, Nis; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem (Juli 2024): Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 21. - 27. July 2024. In: Proceedings of the 41st International Conference on Machine Learning, Proceedings of Machine Learning Research Bd. 235 PMLR. S. 22624-22642 [PDF, 8MB]

Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Haddenhorst, Björn und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Mai 2024): Identifying Copeland Winners in Dueling Bandits with Indifferences. 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Spain, 2. - 4. May 2024. In: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research Bd. 238 PMLR. S. 226-234 [PDF, 522kB]

Kaufmann, Timo ORCID logoORCID: https://orcid.org/0000-0001-5193-8574; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186 und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (2024): Reinforcement Learning from Human Feedback for Cyber-Physical Systems: On the Potential of Self-Supervised Pretraining. International Conference on Machine Learning For Cyber-Physical Systems (ML4CPS 2023), Hamburg, Germany, 29. - 31. March 2023. Niggemann, Oliver; Beyerer, Jürgen; Krantz, Maria und Kühnert, Christian (Hrsg.): In: Technologien für die intelligente Automation, Bd. 18 Cham: Springer Nature Switzerland. S. 11-18 [PDF, 380kB]

Kolpaczki, Patrick; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Muschalik, Maximilian ORCID logoORCID: https://orcid.org/0000-0002-6921-0204 und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (2024): Approximating the Shapley Value without Marginal Contributions. AAAI Conference on Artificial Intelligence 2024, Vancouver, Canada, 20-27 February 2024. Proceedings of the AAAI Conference on Artificial Intelligence. Bd. 38, Nr. 12 S. 13246-13255 [PDF, 2MB]

Brandt, Jasmin; Schede, Elias; Sharma, Shivam; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Tierney, Kevin (Oktober 2023): Contextual Preselection Methods in Pool-based Realtime Algorithm Configuration. Lernen, Wissen, Daten, Analysen (LWDA), Marburg, Germany, 9-11 October 2023. Leyer, Michael und Wichmann, Johannes (Hrsg.): In: Lernen, Wissen, Daten, Analysen (LWDA) Conference Proceedings, Bd. 3630 CEUR-WS.org. S. 492-505 [PDF, 447kB]

Schede, Elias; Brandt, Jasmin; Tornede, Alexander ORCID logoORCID: https://orcid.org/0000-0002-2415-2186; Wever, Marcel ORCID logoORCID: https://orcid.org/0000-0001-9782-6818; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Tierney, Kevin (19. August 2023): A Survey of Methods for Automated Algorithm Configuration (Extended Abstract). Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI 2023), Macao, S.A.R, 19-25 August 2023. In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, S. 6964-6968

Mortier, Thomas ORCID logoORCID: https://orcid.org/0000-0001-9650-9263; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108; Luca, Stijn und Waegeman, Willem ORCID logoORCID: https://orcid.org/0000-0002-5950-3003 (April 2023): On the Calibration of Probabilistic Classifier Sets. 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), Valencia, Spain, 25-27 April, 2023. Ruiz, Francisco; Dy, Jennifer und van de Meent, Jan-Willem (Hrsg.): In: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, Bd. 206 PMLR. S. 8857-8870 [PDF, 764kB]

Brandt, Jasmin; Schede, Elias; Haddenhorst, Björn ORCID logoORCID: https://orcid.org/0000-0002-4023-6646; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Tierney, Kevin (7. Februar 2023): AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. AAAI Conference on Artificial Intelligence, Washington, DC, USA, February, 2023. Proceedings of the AAAI Conference on Artificial Intelligence. Bd. 37, Nr. 10 S. 12355-12363 [PDF, 844kB]

Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem ORCID logoORCID: https://orcid.org/0000-0002-5950-3003 (2023): On Second-Order Scoring Rules for Epistemic Uncertainty Quantification. 40th International Conference on Machine Learning (ICML 2023), Hawaii, USA, 23-29 July, 2023. Krause, Andreas; Brunskill, Emma; Cho, Kyunghyun; Engelhardt, Barbara; Sabato, Sivan und Scarlett, Jonathan (Hrsg.): In: Proceedings of the 40th International Conference on Machine Learning, Bd. 202 PMLR. S. 2078-2091 [PDF, 400kB]

Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem ORCID logoORCID: https://orcid.org/0000-0002-5950-3003 (28. November 2022): Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation. Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, USA, 28 November - 9 December 2022. [PDF, 385kB]

Brandt, Jasmin; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Haddenhorst, Björn ORCID logoORCID: https://orcid.org/0000-0002-4023-6646 und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (28. November 2022): Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, USA, 28 November - 9 December 2022. [PDF, 618kB]

Bengs, Viktor; Saha, Aadirupa und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Juli 2022): Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models. 39th International Conference on Machine Learning, Baltimore, MD, USA, July 17-23 2022. Chaudhuri, Kamalika; Jegelka, Stefanie; Song, Le; Szepesvari, Csaba; Niu, Gang und Sabato, Sivan (Hrsg.): In: Proceedings of the 39th International Conference on Machine Learning, Bd. 162 PMLR. S. 1764-1786 [PDF, 3MB]

Tornede, Alexander ORCID logoORCID: https://orcid.org/0000-0002-2415-2186; Bengs, Viktor und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Juni 2022): Machine Learning for Online Algorithm Selection under Censored Feedback. Thirty-Sixth AAAI Conference on Artificial Intelligence, Virtual, February 22–March 1, 2022. Proceedings of the AAAI Conference on Artificial Intelligence. Bd. 36, Nr. 9 S. 10370-10380

Haddenhorst, Björn ORCID logoORCID: https://orcid.org/0000-0002-4023-6646; Bengs, Viktor und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (7. Dezember 2021): Identification of the Generalized Condorcet Winner in Multi-dueling Bandits. Advances in Neural Information Processing Systems, Virtual, December 7 2021. Ranzato, M.; Beygelzimer, A.; Dauphin, Y.; Liang, P.S. und Vaughan, J. Wortman (Hrsg.): Bd. 34 Curran Associates, Inc.. S. 25904-25916 [PDF, 516kB]

Kolpaczki, Patrick; Bengs, Viktor und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (September 2021): Identifying Top-k Players in Cooperative Games via Shapley Bandits. LWDA’21: Lernen, Wissen, Daten, Analysen, Munich, Germany, 1. - 3. September, 2021. In: Proceedings of the LWDA 2021 Workshops: FGWM, KDML, FGWI-BIA, and FGIR, Bd. 2993 S. 133-144 [PDF, 805kB]

Haddenhorst, Björn ORCID logoORCID: https://orcid.org/0000-0002-4023-6646; Bengs, Viktor; Brandt, Jasmin und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (27. Juli 2021): Testification of Condorcet Winners in dueling bandits. Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, Virtual, July 27-30, 2021. de Campos, Cassio und Maathuis, Marloes H. (Hrsg.): In: Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, Bd. 161 PMLR. S. 1195-1205 [PDF, 875kB]

Mohr, Felix ORCID logoORCID: https://orcid.org/0000-0002-9293-2424; Bengs, Viktor und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Februar 2021): Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model. AAAI Conference on Artificial Intelligence, Virtual, February 2–9, 2021. Proceedings of the AAAI Conference on Artificial Intelligence. Bd. 35, Nr. 14 S. 12373-12381

Bengs, Viktor und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (Juli 2020): Preselection Bandits. 37th International Conference on Machine Learning, Virtual, July 12-18 2020. III, Hal Daumé und Singh, Aarti (Hrsg.): In: Proceedings of the 37th International Conference on Machine Learning, Bd. 119 PMLR. S. 778-787 [PDF, 630kB]

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