[Lisa_teatalk] Tea Talk Today!

Aaron Courville aaron.courville at gmail.com
Thu Feb 16 09:11:19 EST 2012


Hi Gang,

Today we will have a our new post-doc, Heng Luo, tell us about his
previous work. Looking forward to seeing you all there.

When:  Today, 15h00
Where: LISA Lab (AA3256)

Title: "Learning Class-relevant Features and Class-irrelevant Features
via a Hybrid third-order RBM".

Abstract:
Restricted Boltzmann Machines are commonly used in unsupervised
learning to extract features from training data. Since these
features are learned for regenerating training data a classifier based
on them has to be trained. If only a few of the learned features
are discriminative other non-discriminative features will distract the
classifier during the training process and thus waste computing
resources for testing. In this paper, we present a hybrid third-order
Restricted Boltzmann Machine in which class-relevant features (for
recognizing) and class-irrelevant features (for generating only) are
learned simultaneously. As the classification task uses only the
class-relevant features, the test itself becomes very fast. We show
that class-irrelevant features help class-relevant features to focus
on the recognition task and introduce useful regularization effects to
reduce the norms of class-relevant features. Thus there is no need to
use weight-decay for the parameters of this model. Experiments on the
MNIST, NORB and Caltech101 Silhouettes data sets show very promising
results.

If time permits, I will also briefly discuss my paper, "Sparse Group
Restricted Boltzmann Machines".


Cheers,
Aaron

-- 
Aaron C. Courville
Département d’Informatique et
de recherche opérationnelle
Université de Montréal
email:Aaron.Courville at gmail.com


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