3 papers
cs.LG2026
A Complete Characterization of Learnability for Adversarial Noisy Bandits
Steve Hanneke, Kun Wang
We study adversarial noisy bandits given a known function class . In each round, the adversary selects a function , the learner chooses an arm, and…
stat.ML2026
What is Learnable in Valiant's Theory of the Learnable?
Steve Hanneke, Anay Mehrotra, Grigoris Velegkas +1
Valiant's 1984 paper is widely credited with introducing the PAC learning model, but it, in fact, introduced a different model: unlike PAC learning, the learner receives only posit…
cs.LG2026
Regret-Oracle Complexity Tradeoffs in Agnostic Online Learning
Idan Attias, Steve Hanneke, Arvind Ramaswami
Agnostic online learning is classically solved via a reduction to the realizable setting, utilizing Littlestone's Standard Optimal Algorithm (SOA) as a base learner. However, the S…