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Viktor Bengs
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Preference-based online learning with dueling bandits: A survey.
V Bengs, R Busa-Fekete, A El Mesaoudi-Paul, E Hüllermeier
J. Mach. Learn. Res. 22, 7:1-7:108, 2021
942021
A survey of methods for automated algorithm configuration
E Schede, J Brandt, A Tornede, M Wever, V Bengs, E Hüllermeier, ...
Journal of Artificial Intelligence Research 75, 425-487, 2022
452022
Pitfalls of epistemic uncertainty quantification through loss minimisation
V Bengs, E Hüllermeier, W Waegeman
Advances in Neural Information Processing Systems 35, 29205-29216, 2022
35*2022
A survey of reinforcement learning from human feedback
T Kaufmann, P Weng, V Bengs, E Hüllermeier
arXiv preprint arXiv:2312.14925, 2023
302023
Stochastic contextual dueling bandits under linear stochastic transitivity models
V Bengs, A Saha, E Hüllermeier
International Conference on Machine Learning, 1764-1786, 2022
152022
Preselection bandits
V Bengs, E Hüllermeier
International Conference on Machine Learning, 778-787, 2020
15*2020
Pool-based realtime algorithm configuration: A preselection bandit approach
A El Mesaoudi-Paul, D Weiß, V Bengs, E Hüllermeier, K Tierney
Learning and Intelligent Optimization: 14th International Conference, LION …, 2020
142020
On second-order scoring rules for epistemic uncertainty quantification
V Bengs, E Hüllermeier, W Waegeman
International Conference on Machine Learning, 2078-2091, 2023
132023
Uniform approximation in classical weak convergence theory
V Bengs, H Holzmann
arXiv preprint arXiv:1903.09864, 2019
102019
Approximating the shapley value without marginal contributions
P Kolpaczki, V Bengs, M Muschalik, E Hüllermeier
Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 13246 …, 2024
82024
Second-order uncertainty quantification: A distance-based approach
Y Sale, V Bengs, M Caprio, E Hüllermeier
arXiv preprint arXiv:2312.00995, 2023
82023
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget
J Brandt, V Bengs, B Haddenhorst, E Hüllermeier
Advances in Neural Information Processing Systems, 2022
72022
Identification of the generalized Condorcet winner in multi-dueling bandits
B Haddenhorst, V Bengs, E Hüllermeier
Advances in Neural Information Processing Systems 34, 25904-25916, 2021
62021
Non-stationary dueling bandits
P Kolpaczki, V Bengs, E Hüllermeier
arXiv preprint arXiv:2202.00935, 2022
52022
Ac-band: A combinatorial bandit-based approach to algorithm configuration
J Brandt, E Schede, B Haddenhorst, V Bengs, E Hüllermeier, K Tierney
Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 12355 …, 2023
42023
Multi-armed bandits with censored consumption of resources
V Bengs, E Hüllermeier
Machine Learning, 1-24, 2022
42022
Machine learning for online algorithm selection under censored feedback
A Tornede, V Bengs, E Hüllermeier
Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 10370 …, 2022
42022
Testification of condorcet winners in dueling bandits
B Haddenhorst, V Bengs, J Brandt, E Hüllermeier
Uncertainty in Artificial Intelligence, 1195-1205, 2021
42021
Online preselection with context information under the Plackett-Luce model
AE Mesaoudi-Paul, V Bengs, E Hüllermeier
arXiv preprint arXiv:2002.04275, 2020
42020
On testing transitivity in online preference learning
B Haddenhorst, V Bengs, E Hüllermeier
Machine Learning 110, 2063-2084, 2021
32021
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