Machine Learning Summer School (MLSS ), Bordeaux 2011

Machine Learning Summer School (MLSS ), Bordeaux 2011

10 Lectures · Sep 4, 2011

About

The school provides tutorials and practical sessions on basic and advanced topics of machine learning by leading researchers in the field. The summer school is intended for students, young researchers and industry practitioners with an interest in machine learning and a strong mathematical background.

The school addresses the following topics: Learning Theory, Bayesian inference, Monte Carlo Methods, Sparse Methods, Reinforcement Learning, Robot Learning, Boosting, Kernel Methods, Bayesian Nonparametrics, Convex Optimization and Graphical Models.

Detailed information can be found at the summer school homepage.

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Uploaded videos:

Invited Talks

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01:19:50

Low-rank modeling

Emmanuel Candes

Oct 12, 2011

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24604 Views

Invited Talk
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01:01:39

Early language bootstrapping

Emmanuel Dupoux

Oct 12, 2011

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5704 Views

Invited Talk

Tutorials

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03:28:45

Kernel Methods

Bernhard Schölkopf

Oct 12, 2011

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16055 Views

Tutorial
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04:31:12

Monte Carlo Methods

Arnaud Doucet

Oct 12, 2011

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18095 Views

Tutorial
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04:05:13

Bayesian Inference

Peter Green

Oct 12, 2011

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27673 Views

Tutorial
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04:51:54

Bayesian Nonparametrics

Yee Whye Teh

Oct 12, 2011

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35640 Views

Tutorial
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04:49:33

Sparse Methods for Under-determined Inverse Problems

Rémi Gribonval

Oct 12, 2011

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8619 Views

Tutorial
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04:25:58

Convex Optimization

Lieven Vandenberghe

Oct 12, 2011

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21362 Views

Tutorial
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03:41:29

Learning Theory: statistical and game-theoretic approaches

Nicolò Cesa-Bianchi

Oct 12, 2011

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8082 Views

Tutorial
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04:21:17

Graphical Models and message-passing algorithms

Martin J. Wainwright

Oct 12, 2011

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29038 Views

Tutorial