[Colloquium] Saha/Dissertation Defense/Jul 3, 2013

[Margaret Jaffey]

       Department of Computer Science/The University of Chicago

                     *** Dissertation Defense ***


Candidate:  Ankan Saha

Date:  Wednesday, July 3, 2013

Time:  10:00 AM

Place:  Ryerson 277

Title: Optimization Methods in Machine Learning: Theory and
Applications

Abstract:
We look at the integral role played by convex optimization in various
machine learning problems. Over the last few years there has been a
lot of machine learning problems which have a (non)smooth convex
optimization at its core. These problems generally call for fast first
order iterative methods as obtaining the exact minimum is often
impossible and second order methods or higher become prohibitively
expensive even on moderately sized datasets. We look at a few such
optimization problems that arise in different contexts and show that a
class of smoothing strategies due to Nesterov can be applied to these
seemingly very different problems to obtain theoretically faster rates
of convergence than existing methods. Our experimental results
validate the speed and efficacy of our methods and scale significantly
well over a broad range of datasets. This thesis also explores an
often used but understudied optimization algorithm, namely the cyclic
coordinate descent method, and provides a novel theoretical analysis
of the first non-asymptotic convergence rates of cyclic coordinate
descent under certain assumptions. This work also sheds light on some
of the recent advances in online convex optimization to minimize
regret in the presence of smooth unknown functions. We also look at
online learning from the point of view of stability and provide a new
integral framework which encompasses the regret analysis of all
existing algorithms as specific cases of this framework. We
investigate related methods of analysis and the central role played by
optimization in all these seemingly different but connected domains of
machine learning research.

Ankan's advisor is Prof. John Lafferty

Login to the Computer Science Department website for details,
including a draft copy of the dissertation:

 https://www.cs.uchicago.edu/phd/phd_announcements#ankans

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Margaret P. Jaffey            margaret at cs.uchicago.edu
Department of Computer Science
Student Support Rep (Ry 156)               (773) 702-6011
The University of Chicago      http://www.cs.uchicago.edu
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