4 papers
Optimal Mistake Bounds for Transductive Online Learning
Zachary Chase, Steve Hanneke, Shay Moran +1
We resolve a 30-year-old open problem concerning the power of unlabeled data in online learning by tightly quantifying the gap between transductive and standard online learning. In…
Protocols for Verifying Smooth Strategies in Bandits and Games
Miranda Christ, Daniel Reichman, Jonathan Shafer
We study protocols for verifying approximate optimality of strategies in multi-armed bandits and normal-form games. As the number of actions available to each player is often large…
Oblivious Defense in ML Models: Backdoor Removal without Detection
Shafi Goldwasser, Jonathan Shafer, Neekon Vafa +1
As society grows more reliant on machine learning, ensuring the security of machine learning systems against sophisticated attacks becomes a pressing concern. A recent result of Go…
Which Algorithms Have Tight Generalization Bounds?
Michael Gastpar, Ido Nachum, Jonathan Shafer +1
We study which machine learning algorithms have tight generalization bounds. First, we present conditions that preclude the existence of tight generalization bounds. Specifically,…