PRESELECTION BANDITS

von Bengs, Viktor
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 1 of 15 (2021)

Identification of the Generalized Condorcet Winner in Multi-dueling Bandits

von Haddenhorst, Björn
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 31 of 36 (2022)

Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation

von Bengs, Viktor
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 38 of 50 (2023)

Stochastic Contextual Dueling Bandits Under Linear Stochastic Transitivity Models

von Bengs, Viktor
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 3 of 33 (2023)

TESTIFICATION OF CONDORCET WINNERS IN DUELING BANDITS

von Haddenhorst, Björn
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (37. : 2021 : Online) 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021) ; Part 2 of 3 (2022)

Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget

von Brandt, Jasmin
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 27 of 50 (2023)

Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach

von Mesaoudi-Paul, Adil El
Veröffentlicht in LION (14. : 2020) Learning and intelligent optimization (2020)