Deep Learning Symposium
Yoshua Bengio · Yann LeCun · Navdeep Jaitly · Roger Grosse

Thu Dec 8th 02:00 -- 09:30 PM @ Area 1 + 2

Deep Learning algorithms attempt to discover good representations, at multiple levels of abstraction. Deep Learning is a topic of broad interest, both to researchers who develop new algorithms and theories, as well as to the rapidly growing number of practitioners who apply these algorithms to a wider range of applications, from vision and speech processing, to natural language understanding, neuroscience, health, etc. Major conferences in these fields often dedicate several sessions to this topic, attesting the widespread interest of our community in this area of research.

There has been very rapid and impressive progress in this area in recent years, in terms of both algorithms and applications, but many challenges remain. This symposium aims at bringing together researchers in Deep Learning and related areas to discuss the new advances, the challenges we face, and to brainstorm about new solutions and directions.

Author Information

Yoshua Bengio (MILA)
Yann LeCun (Facebook AI Research and New York University)

Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University. He received the Electrical Engineer Diploma from ESIEE, Paris in 1983, and a PhD in Computer Science from Université Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories in Holmdel, NJ in 1988. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU as a professor in 2003, after a brief period as a Fellow of the NEC Research Institute in Princeton. From 2012 to 2014 he directed NYU's initiative in data science and became the founding director of the NYU Center for Data Science. He was named Director of AI Research at Facebook in late 2013 and retains a part-time position on the NYU faculty. His current interests include AI, machine learning, computer perception, mobile robotics, and computational neuroscience. He has published over 180 technical papers and book chapters on these topics as well as on neural networks, handwriting recognition, image processing and compression, and on dedicated circuits for computer perception.

Navdeep Jaitly (Google Brain)
Roger Grosse (University of Toronto)

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