Master Class: Yoshua Bengio (21 Oct - 24 Oct 2013)

Yoshua Bengio (CS PhD, McGill University, 1991) was a post-doc with Michael Jordan at MIT and worked at AT&T Bell Labs before becoming professor at U. Montreal. He wrote two books and around 200 papers, the most cited being in the areas of deep learning, recurrent neural networks, probabilistic learning, NLP and manifold learning. Among the most cited Canadian computer scientists he sat on editorial boards of top ML journals and of the NIPS foundation, holds a Canada Research Chair and an NSERC chair, is a Fellow of CIFAR and has been program/general chair for NIPS. He is driven by his quest for AI through machine learning, involving fundamental questions on deep learning of representations, the geometry of generalization in high-dimension, manifold learning, biologically inspired learning, and challenging applications of ML. He was one of the founders of the area of deep learning in 2006. He was awarded the Urgel-Archambault prize in 2009 and a Canada Research Chair in 2000 (tier 2) and 2006 (tier 1). In August 2013, Google Scholar finds almost 14000 citations to his work, yielding an h-index of 51.

Registration for the Master Class should be done here.

You can find videos of the masterclasses below:

Oct 21: Deep Learning of Representations

Oct 22: Non-local Manifold Learning by Regularized Auto-encoders

Oct 23: Generative Stochastic Networks: How to Get Rid of Approximate Inference over Latent Variables

This event is funded by DeepMind Technologies.

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Previous Events

DateDescription
Wed, 23 Oct 2013 Generative Stochastic Networks: How to Get Rid of Approximate Inference over Latent Variables
Tue, 22 Oct 2013 Non-local Manifold Learning by Regularized Auto-encoders
Mon, 21 Oct 2013 Deep Learning of Representations