This session focuses on three main challenges for bringing deep learning closer to AI.
Dr. Yoshua Bengio, Professor, Universite de Montreal current interests are centered on a quest for AI through machine learning, and include fundamental questions on deep learning and representation learning, the geometry of generalization in high-dimensional spaces, manifold learning, biologically inspired learning algorithms, and challenging applications of statistical machine learning. He is the author of two books and more than 200 publications, with the most influential being from the areas of deep learning, recurrent neural networks, probabilistic learning algorithms, natural language processing, and manifold learning. Dr. Bengio received a Ph.D. from McGill University in 1991, before completing two post-doctoral years at M.I.T. and AT&T Bell Laboratories. He is the Canada Research Chair in Statistical Learning Algorithms.