[Lisa_seminaires] [mila-tous] Reminder 30: [Tea Talk] Devon Hjelm (MSR Montreal + Mila) 10:30am Jean Coutu S1-111

xavier bouthillier xavier.bouthillier at gmail.com
Ven 12 Oct 10:27:16 EDT 2018


Sorry for the late notice. Talk is moved to 3195.

Le ven. 12 oct. 2018 09:59, Michael Noukhovitch <mnoukhov at gmail.com> a
écrit :

> Reminder: talk in 30 minutes!
> Note the different room (in Jean Coutu)
>
> On Tue, Oct 9, 2018, 17:12 Michael Noukhovitch <mnoukhov at gmail.com> wrote:
>
>> 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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