3 papers
cs.LG2026
The Sample Complexity of Multiclass and Sparse Contextual Bandits
Liad Erez, Fan Chen, Alon Cohen +4
We study contextual bandits in the stochastic i.i.d.\ setting, where a learner observes contexts drawn from an unknown distribution, selects actions from a finite set , and aims…
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…