We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori k...
We present a new method for regularized convex optimization and analyze it under both online and stochastic optimization settings. In addition to unifying previously known firstor...
John Duchi, Shai Shalev-Shwartz, Yoram Singer, Amb...
Globally optimal formulations of geometric computer vision problems comprise an exciting topic in multiple view geometry. These approaches are unaffected by the quality of a provid...
—In this paper, we address the spectrum portfolio optimization (SPO) question in the context of secondary spectrum markets, where bandwidth (spectrum access rights) can be bought...
This paper proposes a method to optimize Viterbi beam search based on search error risk minimization in large vocabulary continuous speech recognition (LVCSR). Most speech recogni...