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stat.ML2024
Rate-Preserving Reductions for Blackwell Approachability
Christoph Dann, Yishay Mansour, Mehryar Mohri +2
Abernethy et al. (2011) showed that Blackwell approachability and no-regret learning are equivalent, in the sense that any algorithm that solves a specific Blackwell approachabilit…
cs.GT2024
Strategically-Robust Learning Algorithms for Bidding in First-Price Auctions
Rachitesh Kumar, Jon Schneider, Balasubramanian Sivan
Learning to bid in repeated first-price auctions is a fundamental problem at the interface of game theory and machine learning, which has seen a recent surge in interest due to the…
cs.LG2024
Optimal cross-learning for contextual bandits with unknown context distributions
Jon Schneider, Julian Zimmert
We consider the problem of designing contextual bandit algorithms in the ``cross-learning'' setting of Balseiro et al., where the learner observes the loss for the action they play…