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CALL FOR CONTRIBUTIONS
NIPS workshop on
Distributed Machine Learning and Matrix Computations
December 2014, Montreal, Canada
<a href="http://stanford.edu/~rezab/nips2014workshop/" target="_blank">http://stanford.edu/~rezab/nips2014workshop/</a>
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Description
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The emergence of large distributed matrices in many applications has brought with it a slew of new algorithms and tools. Over the past few years, machine learning and numerical linear algebra on distributed matrices has become a thriving field. Manipulating such large matrices makes it necessary to think about distributed systems issues such as communication cost.
This workshop aims to bring closer researchers in distributed systems and large scale numerical linear algebra to foster cross-talk between the two fields. The goal is to encourage distributed systems researchers to work on machine learning and numerical linear algebra problems, to inform machine learning researchers about new developments on large scale matrix analysis, and to identify unique challenges and opportunities. The workshop will conclude with a session of contributed posters.
Goals of the Workshop
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This workshop will consist of invited talks and paper submissions for a poster session. The target audience of this workshop includes industry and academic researchers interested in machine learning, large distributed systems, numerical linear algebra, and related fields.
Submission deadline will be October 10th, 2014.
Acceptance decisions will be mailed out on or before October 24th, 2014.
Call for Contributions
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The workshop will consist of a mix of presentations and discussions. Researchers who want to contribute should submit their paper to <a href="mailto:distributed-ml-nips14@lists.stanford.edu" target="_blank">distributed-ml-nips14@lists.stanford.edu</a>, in PDF format, following the NIPS style guide.
*** The submission deadline is Friday October 10th ***
The organizers will review all submissions.
Organizers
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Reza Zadeh is a consulting professor at Stanford within the Institute for Computational and Mathematical Engineering.
Website: <a href="http://stanford.edu/~rezab" target="_blank">http://stanford.edu/~rezab</a>
Ameet Talwalkar is an assistant professor of Computer Science at UCLA.
Website: <a href="http://www.cs.berkeley.edu/~ameet/" target="_blank">http://www.cs.berkeley.edu/~ameet/</a>
Ion Stoica is a Professor of Computer Science at UC Berkeley.
Website: <a href="http://www.cs.berkeley.edu/~istoica/" target="_blank">http://www.cs.berkeley.edu/~istoica/</a></pre></div>