[Lisa_seminaires] NEW TIME: UdeM-McGill-MITACS machine learning seminar Tues April 14th, 11:30am, PAA3195

Hugo Larochelle larocheh at iro.umontreal.ca
Jeu 10 Avr 14:32:41 EDT 2008


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


Restricted Boltzmann machines: Performance and behavior on image  
databases and future plans


by Karol Gregor,
California Institute of Technology

Location: Pavillon André Aisenstadt (UdeM), room 3195
Time: April 14th 2008, 11:30am

Inspired by amazing capabilities of cortex and at the same time its  
relatively homogeneous hierarchical structure, it is a worthwhile  
pursuit to develop algorithms that can be repeated in a hierarchical  
fashion and applied to large class of problems including vision,  
speech recognition and motor control. Restricted Boltzmann machines  
are a very capable tool and a good step in this direction. First, I  
will discuss our study of the restricted Boltzmann machines on image  
databases of Scenes and Caltech 256 as applied to bag of words of  
sift features. I will show dependencies on various parameters and  
comparison of performance to other methods. There are other  
interesting conclusions too: For a given amount of labeled data, the  
performance improves if the system is pre-trained on a larger number  
of images; Neurons seem to appear after unsupervised pre-training  
that explicitly represent certain categories (to some extent). Next I  
will discuss a simple experiment with temporal sequences. Then I will  
put this problem into the context of cortical computations and  
outline a plan that I believe is very reasonable to undertake in the  
future.


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