Anzahl der Publikationen: 3
Konferenzbeitrag
Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem ORCID: 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
Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem ORCID: https://orcid.org/0000-0002-5950-3003
(28. November 2022):
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation.
Advances in Neural Information Processing Systems, New Orleans, USA, 28 November - 9 December 2022.
Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle und Cho, Kyunghyun (Hrsg.):
Brandt, Jasmin; Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Haddenhorst, Björn ORCID: https://orcid.org/0000-0002-4023-6646 und Hüllermeier, Eyke ORCID: 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.
Advances in Neural Information Processing Systems, New Orleans, USA, 28 November - 9 December 2022.
Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle und Cho, Kyunghyun (Hrsg.):
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