Hot Stuff


More research highlights and selected recent papers

Deep Learning - an MIT Press book in preparation

KDD'2014 invited tutorial on Scaling Up Deep Learning.

AGI'14 keynote talk slides and video.

ICML'2014 workshop on deep learning for text mining Learning to Represent Natural Language

ICLR: the International Conference on Learning Representations

Canadian AI Conference'2014 Tutorial on Deep Learning of Representations

MLSS'2014 Reykjavik summer school 4.5-hour slides on Deep Learning

SSTiC'2013 summer school 5.5-hour slides on Deep Learning of Representations

AAAI'2013 4-hour tutorial on Deep Learning of Representations

ICML'2012 Tutorial on Representation Learning

ACL'2012 Tutorial on Deep Learning for NLP (without Magic)

VIDEO of introductory talk at ICML'2012 Representation Learning workshop

My slides for the IPAM GSS'2012 Summer School on Representation Learning

Slides of my BTAS'2013 plenary talk on Deep Learning towards AI

UCL Masterclass lectures Oct. 21-23 2013 (lecture 1 pdf) (lecture 2 pdf) (lecture 3 pdf) (videos)

2013 paper on challenges of deep learning and ideas to attack them

2012 Review paper on unsupervised feature learning and deep learning

2012 review paper on Practical recommendations for gradient-based training of deep architectures

2009 Review paper / monograph on learning algorithms for deep architectures (pdf)

YB interviewed by Wired on Deep Learning and AI, June 27th, 2013.

YB interviewed at Radio-Canada national French-language TV, broadcast April 7, 2013.

 

Yoshua Bengio  


Yoshua Bengio
Full Professor
Department of Computer Science and Operations Research
Canada Research Chair in Statistical Learning Algorithms
<my first name> (dot) <my last name> (at sign) umontreal (dot) ca

 

 

To research highlights and selected recent papers



Profile

Yoshua Bengio is Full Professor of the Department of Computer Science and Operations Research, head of the Machine Learning Laboratory (LISA), CIFAR Fellow in the Neural Computation and Adaptive Perception program,  Canada Research Chair in Statistical Learning Algorithms, and he also holds the NSERC-Ubisoft industrial chair. His main research ambition is to understand principles of learning that yield intelligence. He teaches a graduate course in Machine Learning (IFT6266) and supervises a large group of graduate students and post-docs. His research is widely cited (over 16000 citations found by Google Scholar in early 2014, with an H-index of 55).

Yoshua Bengio is currently action editor for the Journal of Machine Learning Research, editor for Foundations and Trends in Machine Learning, and has been associate editor for the Machine Learning Journal and the IEEE Transactions on Neural Networks.

Yoshua Bengio was Program Chair for NIPS'2008 and General Chair for NIPS'2009 (NIPS is the flagship conference in the areas of learning algorithms and neural computation). Since 1999, he has been co-organizing the Learning Workshop with Yann Le Cun, with whom he has also created the International Conference on Representation Learning (ICLR). He has also organized or co-organized numerous other events, such as the ICML'2012 Representation Learning Workshop, the NIPS'2011 Deep Learning and Unsupervised Feature Learning Workshop, the NIPS'2010 Deep Learning and Unsupervised Feature Learning Workshop, the ICML'2009 Workshop on Learning Feature Hierarchies and the NIPS'2007 Deep Learning Workshop.


Connectivity
From Artificial Intelligence to the Collective


 
Contact

E-mail (best way to reach me):
    <my first name> (dot) <my last name> (at sign) umontreal (dot) ca

Phone:
  Office: 514 343 6804
  Department Fax: 514 343 5834
  Cell phone: upon request

Snail-mail:
  Regular mail should go to this post-office box:
Département d’Informatique et de recherche opérationnelle
Université de Montréal, P.O. Box 6128, Centre-Ville Branch
Montréal (QC), H3C 3J7, Canada
  Express mail should go to this street address:
Département d’Informatique et de recherche opérationnelle
Université de Montréal, 2920 chemin de la Tour, suite 2194,
Montréal (QC), H3T 1J4, Canada

In person:
2920 chemin de la Tour, Montréal,
Pavillon André-Aisenstadt, 3rd floor,
office in room 3339 or lab in room 3256


 


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