[Colloquium] Reminder: Sam Roweis Talk Today @ 10am TTI-C

[Katherine Cumming]

Guest Speaker @ TTI-C
 
Speaker:  Sam Roweis,  Department of Computer Science, U Toronto & MIT
CSAIL
Speaker's homepage:  http://www.cs.toronto.edu/~roweis/
 
Monday, April 18th @ 10am
Location:  TTI-C Conference Room
Title:  Neighbourhood Components Analysis
Abstract:
Say you want to do K-Nearest Neighbour classification. Besides selecting
K, you also have to chose a distance function, in order to define
"nearest". I'll talk about a novel method for learning, from the data
itself, a Mahalanobis distance measure to be used in KNN classification.
The learning algorithm, Neighbourhood Components Analysis (NCA),
directly maximizes a stochastic variant of the leave-one-out KNN score
on the training set. Of course, the resulting classification model is
non-parametric, making no strong prior assumptions about the shape of
the class distributions or the boundaries between them. NCA can also
learn a low-dimensional linear embedding of labeled data that can be
used for very cheap and fast classification in high dimensions or even
for data visualization. If time permits, I'll also talk about newer work
on learning the same kind of distance metric for use inside a Gaussian
Kernel SVM classifier. (Joint work with Jacob Goldberger) 
If you have questions, or would like to meet the speaker, please contact
Katherine at 4-1994 or kcumming at tti-c.org. For information on future
TTI-C talks or events, please go to the TTI-C Events
<http://ttic.uchicago.edu/events/events_dyn.php>  page. 
 
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