[Lisa_seminaires] [Bigger Room CHANGE] [mila-tous] [Tea Talk] Hugo Larochelle (Mila + Brain) Fri November 9 2018 10:30 AM Z-330

Pablo Fonseca palefo at gmail.com
Ven 9 Nov 15:46:12 EST 2018


The recording of today's tea talk is here: https://bluejeans.com/s/dlayJ/

Pablo

On Fri, Nov 9, 2018 at 10:38 AM Pablo Fonseca <palefo at gmail.com> wrote:

> The streaming link is: The streaming link is
> https://bluejeans.com/910827731/webrtc
> Pablo Fonseca
>
>
> On Fri, Nov 9, 2018 at 9:42 AM Rim Assouel <rim.assouel at gmail.com> wrote:
>
>> Last minute change for a bigger room (this one has a capacity of 130 so
>> we should be fine).
>>
>> The talk will happen in Z-330, this is the Claire McNicoll building !
>>
>> See you there,
>>
>> Rim & Sai
>>
>>
>>
>> On Mon, Nov 5, 2018 at 9:33 AM <rim.assouel at gmail.com> wrote:
>>
>>> This week we have *Hugo Larochelle* from * Mila + Brain* giving a talk
>>> on *Fri November 9 2018* at *10:30 AM* in room *JC S1-111*
>>>
>>> Will this talk be streamed <https://mila.bluejeans.com/809027115/webrtc>?
>>> Yes
>>> Recorded? Yes
>>>
>>> Feel like learning to learn ? Hugo will teach you the good way, this
>>> Friday,  one shot at a time ;)
>>>
>>> See you there!
>>> Rim and Sai
>>>
>>> *TITLE* Few-Shot Learning with Meta-Learning: Progress Made and
>>> Challenges Ahead.
>>>
>>> *KEYWORDS*
>>>
>>> *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. His long time nemesis is Aaron Courville. Finally, he has a
>>> popular online course on deep learning and neural networks, freely
>>> accessible on YouTube.
>>>
>>> --
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>>>
>>
>>
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>
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