Deep Learning Symposium

DATE: Thursday, December 10, 2015 

LOCATION: Convention Center, Montreal, QC, CANADA 

SCHEDULE: ckick here 



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.

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.


We have invited a relatively small number of leading experts in the field to serve as our Program Committee (PC). PC members will then propose papers and speakers (selected outside their own groups) for the symposium, based on papers they have read or talks they have attended recently. In order to make authors’ most recent work more easily accessible, we make available a recommendation website that let authors upload their papers, while enabling public comments as well as private comments among the PC members.

The schedule will be divided into several parts, grouping work by area. Each talk will be followed by a Q&A session, with questions taken from the audience, our PC members as well as via public polls which will be opened a week before the event.

In addition to invited talks, we will also have panel discussions concluding each session, bringing together the invited speakers, the organizers and leaders in the field.


The schedule is available here.

Yoshua Bengio                  Marc'Aurelio Ranzato         Honglak Lee               Max Welling                     Andrew Ng
University of Montreal        Facebook AI Research       University of Michigan  University of Amsterdam    BAIDU Research


Ryan Adams - Harvard Univ.

Francis Bach - INRIA

Samy Bengio - Google

Phil Blunsom - Oxford & Google

Antoine Bordes - Facebook

Kyunghyun Cho - NYU

Ronan Collobert - Facebook

Aaron Courville - Univ. Montreal

Trevor Darrell - Berkeley

Nando De Freitas - Oxford & Google

Ian Goodfellow - Google

Brian Kingsbury - IBM

Hugo Larochelle - Univ. Sherbrooke

Roland Memisevic - Univ. Montreal

Tomas Mikolov - Facebook

Ruslan Salakhutdinov - Univ. Toronto

Ilya Sutskever - Google

Richard Sutton - Univ. of Alberta

Jason Weston - Facebook

Chris Williams - Univ. Edinburgh

Alan Yuille - UCLA

Richard Zemel - Univ. of Toronto

Andrew Zisserman - Oxford & Google