16 citations · 28 across the 2 of their papers we have counts for
3 papers
Blackwell Approachability and Low-Regret Learning are Equivalent
Jacob Abernethy, Peter L. Bartlett, Elad Hazan
We consider the celebrated Blackwell Approachability Theorem for two-player games with vector payoffs. We show that Blackwell's result is equivalent, via efficient reductions, to t…
A Stochastic View of Optimal Regret through Minimax Duality
Jacob Abernethy, Alekh Agarwal, Peter L. Bartlett +1
We study the regret of optimal strategies for online convex optimization games. Using von Neumann's minimax theorem, we show that the optimal regret in this adversarial setting is…
Local Rademacher complexities
Peter L. Bartlett, Olivier Bousquet, Shahar Mendelson
We propose new bounds on the error of learning algorithms in terms of a data-dependent notion of complexity. The estimates we establish give optimal rates and are based on a local…