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Stochastic Gradient Methods

February 24 - 28, 2014

Organizing Committee | Scientific Overview | Speaker List

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Organizing Committee

Leon Bottou (Microsoft Research, CS)
Yann LeCun (New York University, Canadian Institute for Advanced Research)
Angelia Nedich (University of Illinois at Urbana-Champaign)
Ben Recht (University of California, Berkeley (UC Berkeley))
Stephen Wright (University of Wisconsin-Madison, Computer Science)

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Scientific Overview

Stochastic gradients (SG) methods have a long history in optimization, dating to the work of Robbins and Monro in 1951. The appeal of these methods is due largely to their ability to cope efficiently and robustly with inexact information about the underlying optimization problem. Recently, there has been an outburst of research activity on SG methods, driven in part by their remarkable suitability to machine learning models involving huge data sets. A prominent feature of these methods is their ability to make progress by examining only a small fraction of the data set rather than scanning the entire data set - an operation that is prohibitively expensive in many modern applications.

This workshop will address various topics in the theory, implementation, and practice of SG methods, possibly including the following: applications to nonconvex problems and regularized objectives; parallel implementations; hybridization of SG methods with other optimization techniques; and use of SG methods in deep learning, latent variable models, and other settings.

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Confirmed Speakers

Alekh Agarwal (Microsoft Research)
Francis Bach (Institut National de Recherche en Informatique Automatique (INRIA))
Dimitri Bertsekas (Massachusetts Institute of Technology)
David Blei (Princeton University)
Leon Bottou (Microsoft Research)
John Duchi (University of California, Berkeley (UC Berkeley))
John Langford (Microsoft Research)
Yann LeCun (New York University)
David McAllester (TTI-Chicago)
Noboru Murata (Waseda University)
Deanna Needell (Claremont McKenna College)
Jorge Nocedal (Northwestern University)
Asuman Ozdaglar (Massachusetts Institute of Technology)
Chris Re (Stanford University)
Ben Recht (University of California, Berkeley (UC Berkeley))
Peter Richtarik (University of Edinburgh)
Mark Schmidt (Simon Fraser University)
Yoram Singer (Google Inc.)
Steve Smale (City University of Hong Kong)
James Spall (Johns Hopkins University)
Nathan Srebro (TTI-Chicago)
Rachel Ward (University of Texas at Austin)
Jason Weston (Facebook)
Stephen Wright (University of Wisconsin-Madison)
Lin Xiao (Microsoft Research)

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Contact Us:

Institute for Pure and Applied Mathematics (IPAM)
Attn: SGM2014
460 Portola Plaza
Los Angeles CA 90095-7121
Phone: 310 825-4755
Fax: 310 825-4756
Website: http://www.ipam.ucla.edu/programs/sgm2014/

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