[Compstats] Reminder : Google UW distinguished seminar: Shai Shalev-Shwartz tomorrow

Shai Ben-David shai at cs.uwaterloo.ca
Wed Jul 14 21:03:20 EDT 2010

The next talk in the Google distinguished seminar series in machine learning
will take place tomorrow, Thursday, at 2:15 in DC 1304.

Title: Machine Learning in the Data Revolution Era
Speaker: Shai Shalev-Shwartz (Hebrew University, Israel)

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 a 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. Paper of his
have won best paper awards in the most important machine learning
conferences ( NIPS, ICML and COLT).

> 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.

> Shai

Shai Ben-David
David R. Cheriton School of Computer Science University of Waterloo,
 Waterloo, Ontario Canada N2L 3G1
Web: http://www.cs.uwaterloo.ca/~shai
Telephone: 1-519-888-4567x37523
Fax: 1-519-885-1208
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