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cs.LG2025
Sample Complexity of Agnostic Multiclass Classification: Natarajan Dimension Strikes Back
Alon Cohen, Liad Erez, Steve Hanneke +4
The fundamental theorem of statistical learning states that binary PAC learning is governed by a single parameter -- the Vapnik-Chervonenkis (VC) dimension -- which determines both…
cs.LG2025
Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback
Orin Levy, Liad Erez, Alon Cohen +1
We present regret minimization algorithms for the contextual multi-armed bandit (CMAB) problem over actions in the presence of delayed feedback, a scenario where loss observati…
cs.LG2025
From Contextual Combinatorial Semi-Bandits to Bandit List Classification: Improved Sample Complexity with Sparse Rewards
Liad Erez, Tomer Koren
We study the problem of contextual combinatorial semi-bandits, where input contexts are mapped into subsets of size of a collection of possible actions. In each round, the…