[Colloquium] FW: Guest Speaker Announcement

[Ponda Barnes]

Reminder!!
 
 
Guest Speaker
 
Presented by: Toyota Technological Institute at Chicago
 
Speaker: Greg Shakhnarovich
Speaker's home page: http://people.csail.mit.edu/gregory/
 
Date: Tuesday, March 27, 2007
Time: 10:00 am
Location: TTI-C Conference room
 
 
Title: Learning Task-Specific Similarity
 
 
Abstract:
 
    The notion of similarity is fundamental in machine learning.  The
ability to assess similarity, and to find in a database examples similar to
a given instance, is central to many statistical
    learning methods.  Similarity is commonly modeled in terms of a distance
function in the input space.  However, such a definition may not capture the
concept of similarity relevant to the task at
    hand.  In this talk, I will describe an approach to learning similarity
from user-provided examples of what is deemed similar   (and, optionally,
dissimilar).  I will show how to construct, using
    a greedy algorithm inspired by boosting, an embedding of the data into a
weighted binary space, where a simple metric approximates the original
similarity concept.  This approach provides a means for data
    compression focused on preserving relevant features, and enables
efficient search with respect to user-defined similarity in very large
databases.  I will show how this makes example-based learning
    work well in some of the problems in computer vision for which it was
previously deemed infeasible.
 
If you have any questions or would like to meet the speaker, please contact
Ponda Barnes at pondabarnes at tti-c.org
For future TTI-C talks and events, please go to
http://ttic.uchicago.edu/cal/month.php
 
 
 
 
 
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