[Lisa_seminaires] [Tea Talk] Geoff Gordon (MSR Montreal) Fri September 7 2018 10:30 AA3195

Michael Noukhovitch mnoukhov at gmail.com
Mar 4 Sep 17:55:15 EDT 2018


This week we are super lucky to have *Geoff Gordon*, Research Director of *
MSR Montreal * giving a talk on *Fri September 7 2018* at *10:30* in room
*AA3195*

Will this talk be streamed <https://mila.bluejeans.com/809027115/webrtc>?
*No*

Geoff will be available to meet in the afternoon! Sign up here
<https://calendar.google.com/calendar/selfsched?sstoken=UVBVTVF0X25Nd09LfGRlZmF1bHR8ZWQ5MmNlYWMxODI4OWVkNmUzNGU3OTE4ZDExMGI0YTk>

Knowing that this talk is likely awesome and that you probably come to
talks given they're awesome, you're probably going to the talk! Good choice!
Michael

*TITLE* Neural Networks and Bayes Rule

*KEYWORDS* Deep Graphical Models, Reasoning with NNs

*ABSTRACT*
Relational or structured reasoning is an important current research
challenge. The classical approach to this challenge is a templated
graphical model: highly expressive, with well-founded semantics, but (at
least naively) difficult to scale up, and difficult to combine with the
most effective supervised learning methods. More recently, researchers have
designed many different deep network architectures for structured reasoning
problems, with almost the flip set of advantages and disadvantages. Can we
get the best of both worlds? That is, can we design deep nets that look
more like graphical models, or graphical models that look more like deep
nets, so that we get a framework that is both practical and "semantic"?
This talk will take a look at some progress toward such a hybrid framework.

*BIO*
Dr. Gordon is the Research Director of Microsoft Research Montreal. He is
on leave as a Professor in the Department of Machine Learning at Carnegie
Mellon University, where he has also served as Interim Department Head and
as Associate Department Head for Education. His research interests include
artificial intelligence, statistical machine learning, game theory,
multi-robot systems, and planning in probabilistic, adversarial, and
general-sum domains. His previous appointments include Visiting Professor
at the Stanford Computer Science Department and Principal Scientist at
Burning Glass Technologies in San Diego. Dr. Gordon received his B.A. in
Computer Science from Cornell University in 1991, and his Ph.D. in Computer
Science from Carnegie Mellon University in 1999.
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