150 citations · 219 across the 3 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.LG2011★ 150 cited
Better Mini-Batch Algorithms via Accelerated Gradient Methods
Andrew Cotter, Ohad Shamir, Nathan Srebro +1
Mini-batch algorithms have been proposed as a way to speed-up stochastic convex optimization problems. We study how such algorithms can be improved using accelerated gradient metho…