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pro vyhledávání: '"Derr, Rabanus"'
We study games in which a leader makes a single commitment, and then multiple followers (each with a different utility function) respond. In particular, we study ambiguous commitment strategies in these games, in which the leader may commit to a set
Externí odkaz:
http://arxiv.org/abs/2409.05608
Supervised learning has gone beyond the expected risk minimization framework. Central to most of these developments is the introduction of more general aggregation functions for losses incurred by the learner. In this paper, we turn towards online le
Externí odkaz:
http://arxiv.org/abs/2406.02292
Autor:
Derr, Rabanus, Williamson, Robert C.
Machine learning is about forecasting. Forecasts, however, obtain their usefulness only through their evaluation. Machine learning has traditionally focused on types of losses and their corresponding regret. Currently, the machine learning community
Externí odkaz:
http://arxiv.org/abs/2401.14483
Autor:
Derr, Rabanus, Williamson, Robert C.
In literature on imprecise probability little attention is paid to the fact that imprecise probabilities are precise on a set of events. We call these sets systems of precision. We show that, under mild assumptions, the system of precision of a lower
Externí odkaz:
http://arxiv.org/abs/2302.03522
Strict frequentism defines probability as the limiting relative frequency in an infinite sequence. What if the limit does not exist? We present a broader theory, which is applicable also to random phenomena that exhibit diverging relative frequencies
Externí odkaz:
http://arxiv.org/abs/2302.03520
Autor:
Derr, Rabanus, Williamson, Robert C.
Fair Machine Learning endeavors to prevent unfairness arising in the context of machine learning applications embedded in society. Despite the variety of definitions of fairness and proposed "fair algorithms", there remain unresolved conceptual probl
Externí odkaz:
http://arxiv.org/abs/2207.13596
Publikováno v:
In International Journal of Approximate Reasoning May 2024 168
Akademický článek
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Autor:
Derr R; Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany., Williamson RC; Department of Computer Science, University of Tübingen, Germany and Tübingen AI Center, 72076 Tübingen, Germany.
Publikováno v:
Entropy (Basel, Switzerland) [Entropy (Basel)] 2023 Aug 31; Vol. 25 (9). Date of Electronic Publication: 2023 Aug 31.