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stat.ML2024★ 1 cited
An Information-Theoretic Approach to Generalization Theory
Borja Rodríguez-Gálvez, Ragnar Thobaben, Mikael Skoglund
We investigate the in-distribution generalization of machine learning algorithms. We depart from traditional complexity-based approaches by analyzing information-theoretic bounds t…
stat.ML2024
Chained Information-Theoretic bounds and Tight Regret Rate for Linear Bandit Problems
Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering +1
This paper studies the Bayesian regret of a variant of the Thompson-Sampling algorithm for bandit problems. It builds upon the information-theoretic framework of [Russo and Van Roy…