[Compstats] Google UW distinguished seminar: Shai Shalev-Shwartz (Moved to Thursday July 15)
shai at cs.uwaterloo.ca
Wed Jul 7 17:07:58 EDT 2010
Please note the change in time and location for this talk next week.
Let me add that Shai Shalev-Shwartz is a real rising star in the area
of theoretical machine learning. Shalev-Shwartz has distinguished
himself from many in that community by having made algorithmic contributions
that are highly significant for machine learning practitioners.
> Title: Machine Learning in the Data Revolution Era
> Speaker: Shai Shalev-Shwartz (Hebrew University, Israel)
> Date: Thursday, July 15
> Time: 2:15pm
> Location: DC1304
> Machine learning is playing a central role in the digital revolution,
> in which massive and never-ending data is collected from various
> sources such as online commerce, social networking, and online
> collaboration. This large amount of data is often noisy or partial.
> In this talk I will present learning algorithms appropriate for this
> new era: algorithms that not only can handle massive amounts of data
> but can also leverage large data sets to reduce the required runtime;
> and algorithms that can use the multitude of examples to compensate
> for lack of full information on each individual example.
> Shai Shalev-Shwartz is on the faculty of the Department of Computer
> Science and Engineering at the Hebrew university of Jerusalem, Israel.
> Dr. Shalev-Shwartz received the PhD degree in computer science from
> the Hebrew university, in 2007. Between 2007-2009 he was a research
> assistant professor at Toyota Technological Institute at Chicago. Shai
> has written more than 40 research papers, focusing on learning theory,
> online prediction, optimization techniques, and practical algorithms.
Paper of his have won best paper awards in the most important machine
learning conferences ( NIPS, ICML and COLT).
> He served as a program committee member for the COLT conference in
> 2008-2010, a program committee member for ALT in 2009, and he is part
> of the editorial boards of the Journal of Machine Learning Research
> (JMLR) and the Machine Learning Journal (MLJ).
David R. Cheriton School of Computer Science University of Waterloo,
Waterloo, Ontario Canada N2L 3G1
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