PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Composite Objective Mirror Descent
John Duchi, Shai Shalev-Shwartz, Yoram Singer and Ambuj Tewari
In: COLT 2010(2010).

Abstract

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 firstorder algorithms, such as the projected gradient method, mirror descent, and forwardbackward splitting, our method yields new analysis and algorithms. We also derive specific instantiations of our method for commonly used regularization functions, such as ℓ1, mixed norm, and trace-norm.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:7140
Deposited By:Shai Shalev-Shwartz
Deposited On:06 March 2011