160 citations · 1.5k across the 122 of their papers we have counts for
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cs.LG2011★ 57 cited
On the Universality of Online Mirror Descent
Nathan Srebro, Karthik Sridharan, Ambuj Tewari
We show that for a general class of convex online learning problems, Mirror Descent can always achieve a (nearly) optimal regret guarantee.
cs.IT2011★ 51 cited
Orthogonal Matching Pursuit with Replacement
Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon
In this paper, we consider the problem of compressed sensing where the goal is to recover almost all the sparse vectors using a small number of fixed linear measurements. For this…
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…