[Lisa_seminaires] [Tea Talk] Devon Hjelm (MSR Montreal + Mila) Fri October 12 2018 10:30 JC S1-111

Michael Noukhovitch mnoukhov at gmail.com
Mar 9 Oct 17:12:44 EDT 2018


This week we have our very own *Devon Hjelm * from * MSR Montreal x Mila *
giving a talk on *Friday October 12 2018* at *10:30* in room *Jean Coutu
S1-111*

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

Maximize your own information and come learn at this talk!
Michael

*TITLE* Learning representations with Deep InfoMax

*KEYWORDS *representation learning, unsupervised learning, adversarial
learning

*ABSTRACT*
In this work, we perform unsupervised learning of representations by
maximizing mutual information between an input and the output of a deep
neural network encoder. Importantly, we show that structure matters:
incorporating knowledge about locality of the input to the objective can
greatly influence a representation’s suitability for downstream tasks. We
further control characteristics of the representation by matching to a
prior distribution adversarially. Our method, which we call Deep InfoMax
(DIM), outperforms a number of popular unsupervised learning methods and
competes with fully-supervised learning on several classification tasks.
DIM opens new avenues for unsupervised learning of representations and is
an important step towards flexible formulations of representation-learning
objectives for specific end-goals (https://arxiv.org/abs/1808.06670)

*BIO*
Devon Hjelm is a researcher at Microsoft Research Montreal and an Adjunct
Professor at MILA. He did his postdoc at MILA where he focused on
adversarial learning and generative models. His current research focuses on
using mutual information estimation objectives in representation learning
for applications in computer vision, natural language, and RL.
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