[Lisa_seminaires] REMINDER: UdeM-McGill-MITACS machine learning seminar Fri March 14th, 12:00pm, MC437 NEW TIME!

Hugo Larochelle larocheh at iro.umontreal.ca
Jeu 13 Mar 10:34:40 EDT 2008


Next week's seminar (see http://www.iro.umontreal.ca/article.php3? 
id_article=107&lang=en):


Discriminative Methods with Structure


by Simon Lacoste-Julien,
Computer Science
University of California

Location: McConnell Engineering Building (McGill), room 437
Time: March 14th 2008, 12h00

Real world problems such as machine translation involve complex
dependencies. Generative models have provided an elegant and flexible
framework to model those dependencies, but they appear to lack
robustness to model misspecification compared to discriminative
models for classification. In this talk, we present methods for
leveraging the advantages of generative models in the discriminative
framework.

In the first part of the talk, we tackle the word alignment problem
from natural language processing. We formulate it as a weighted
bipartite matching problem and show how to learn the weights by using
a large-margin approach for structured prediction. By providing a
flexible discriminative modeling framework, we were able to cut the
Alignment Error Rate in half compared to the previous best performing
generative models for word alignment.

In the second part of the talk, we study probabilistic topic models
which have been popular for modeling latent structures in text
documents (as bag of words) or images (as bag of visual words). They
are usually trained as generative models with maximum likelihood
estimation, though this could be suboptimal if one is interested in
doing classification. In contrast, we present a discriminative
version of the Latent Dirichlet Allocation (LDA) model which attempts
to uncover the latent structure in the documents while optimizing its
predictive power for the task of classification. We present results
in the domains of document classification and scene categorization.

(joint work with Fei Sha, Ben Taskar, Dan Klein and Michael I. Jordan)


Plus d'informations sur la liste de diffusion Lisa_seminaires