[Colloquium] Today: Sindhwani/Dissertation Defense/8-3-07

[Margaret Jaffey]

This is a reminder about Vikas Sindhwani's Dissertation Defense this  
afternoon.

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			Department of Computer Science/The University of Chicago

					*** Dissertation Defense ***

Candidate:  Vikas Sindhwani

Date:  Friday, August 3, 2007

Time and Location:  2:30 p.m. in Ryerson 276

Title:  On Semi-supervised Kernel Methods

Abstract:
In many applications of machine learning, abundant amounts of data  
can be cheaply and automatically collected. However, manual labeling  
for the purposes of training learning algorithms is often a slow,  
expensive, and error-prone process.  The goal of semi-supervised  
learning is to utilize a large collection of unlabeled data jointly  
with a few labeled examples for improving generalization performance  
(e.g., in classification, regression tasks).  In this thesis, we  
present families of algorithms: Manifold Regularization, Low-density  
Methods and Co-regularization, for extending kernel methods (such as  
Support Vector Machines) for Semi-supervised learning. These  
algorithms are based on different operating assumptions on the  
structure and geometry of the probability distribution underlying the  
data. Empirical results on a variety of learning tasks, including  
large-scale text categorization, confirm that this body of algorithms  
obtain state-of-the-art performance.

Candidate's Advisor:  Prof. Partha Niyogi

A draft copy of Mr. Sindhwani's dissertation is available in Ry 156.

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Margaret P. Jaffey                             margaret at cs.uchicago.edu
Department of Computer Science
Student Support Rep (Ry 161A)        (773) 702-6011
The University of Chicago                  http://www.cs.uchicago.edu
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