[Lisa_seminaires] [mila-tous] [Tea Talk] Hugo Larochelle (Mila + Brain) Fri January 25 2019 10h30 Mila Auditorium

Pablo Fonseca palefo at gmail.com
Ven 25 Jan 09:56:41 EST 2019


Just a reminder, this happens in ~half an hour
The talk is going to be streamed at:
https://mila.bluejeans.com/4862024040/webrtc
<https://mila.bluejeans.com/4862024040/webrtc>


On Mon, Jan 21, 2019 at 11:09 AM Rim Assouel <rim.assouel at gmail.com> wrote:

> This week we have * Hugo Larochelle* from * Mila + Brain * giving a talk
> on * (Part II) Few-Shot Learning with Meta-Learning: Progress Made and
> Challenges Ahead* at * 10h30* in room * Mila Auditorium*.
>
> Will this talk be streamed <https://mila.bluejeans.com/809027115/webrtc>?
> yes
>
> Feel like learning to learn again  ? Hugo will teach you another way, this
> Friday,  one shot at a time ;)
>
> See you there!
> Pablo, Sai and Rim
>
> Tea Talks website :
> https://sites.google.com/lisa.iro.umontreal.ca/tea-talk-recordings
>
> *TITLE* (Part II) Few-Shot Learning with Meta-Learning: Progress Made and
> Challenges Ahead
>
> *ABSTRACT*
> A lot of the recent progress on many AI tasks was enable in part by the
> availability of large quantities of labeled data. Yet, humans are able to
> learn concepts from as little as a handful of examples. Meta-learning is a
> very promising framework for addressing the problem of generalizing from
> small amounts of data, known as few-shot learning. In meta-learning, our
> model is itself a learning algorithm: it takes as input a training set and
> outputs a classifier. For few-shot learning, it is (meta-)trained directly
> to produce classifiers with good generalization performance for problems
> with very little labeled data. In this talk, I'll present an overview of
> the recent research that has made exciting progress on this topic
> (including my own) and will discuss the challenges as well as research
> opportunities that remain.
>
> *BIO*
> Hugo Larochelle is Research Scientist at Google Brain and lead of the
> Montreal Google Brain team. He is also a member of Yoshua Bengio's Mila and
> an Adjunct Professor at the Université de Montréal. Previously, he was
> Associate Professor at the University of Sherbrooke. He also co-founded
> Whetlab, which was acquired in 2015 by Twitter, where he then worked as a
> Research Scientist in the Twitter Cortex group. From 2009 to 2011, he was
> also a member of the machine learning group at the University of Toronto,
> as a postdoctoral fellow under the supervision of Geoffrey Hinton. He
> obtained his Ph.D. at the Université de Montréal, under the supervision of
> Yoshua Bengio. He has the best hair in machine learning academia (not his
> words). Finally, he has a popular online course on deep learning and neural
> networks, freely accessible on YouTube.
>
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