[Room CHANGE] [mila-tous] [Tea Talk] Hugo Larochelle (Mila + Brain) Fri November 9 2018 10:30 AM AA 3195
The room has changed ( I updated the calendar). This will happen in AA - 3195 : we will add as many chairs as possible.
Le 8 nov. 2018 à 18:07, Alex Lamb <alex6200@gmail.com> a écrit :
"JC S1-111"
This is jean-couteau on the udem campus?
On Mon, Nov 5, 2018 at 9:33 AM <rim.assouel@gmail.com <mailto:rim.assouel@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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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@gmail.com <mailto:rim.assouel@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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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@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@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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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@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@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@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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participants (2)
-
Pablo Fonseca -
Rim Assouel