[Colloquium] TTIC Talks: Justin Domke, RIT

[Liv Leader]

REMINDER:

When:     Friday, April 6 @ 11 a.m.

Where:    TTIC, 6045 S. Kenwood Avenue, Room 526

Who:       Justin Domke, RIT

Title:        Beating the Likelihood: Marginalization-Based Parameter
Learning in Graphical Models

Abstract: Probabilistic graphical models represent uncertainty in many
domains, such as error-correcting codes, computational biology, or sensor
networks.  Traditional likelihood-based learning of such models faces
challenges of computational complexity and robustness to model error.  This
talk will discuss methods that directly maximize a measure of the accuracy
of predicted marginals, in the context of a particular approximate
inference algorithm.  Experiments on computer vision problems suggest that
marginalization-based learning, by compensating for both model and
inference approximations at training time, can perform better than
likelihood-based approximations when the model being fit is approximate in
nature.

Host: Raquel Urtasun, rurtasun at ttic.edu



-- 
Liv Leader
Human Resources Coordinator

Toyota Technological Institute Chicago
6045 S Kenwood Ave
Chicago, IL 60637
Phone- (773) 702-5033
Fax-     (773) 834-9881
Email-  lleader at ttic.edu <jam at ttic.edu>
Web-   www.ttic.edu
<http://www.ttic.edu/>
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