16 citations · 28 across the 2 of their papers we have counts for
2 papers
stat.ML2011★ 12 cited
Online Learning: Stochastic and Constrained Adversaries
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and th…
cs.LG2009★ 16 cited
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…