Machine Learning Summer School (MLSS ), Bordeaux 2011
10 Videos · 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.
Videos
Invited Talks
Low-rank modeling
Oct 12, 2011 24653 views
Early language bootstrapping
Oct 12, 2011 5731 views
Tutorials
Bayesian Nonparametrics
Oct 12, 2011 35900 views
Bayesian Inference
Oct 12, 2011 27930 views
Learning Theory: statistical and game-theoretic approaches
Oct 12, 2011 8143 views
Kernel Methods
Oct 12, 2011 16119 views
Sparse Methods for Under-determined Inverse Problems
Oct 12, 2011 8705 views
Monte Carlo Methods
Oct 12, 2011 18167 views
Graphical Models and message-passing algorithms
Oct 12, 2011 29146 views
Convex Optimization
Oct 12, 2011 21469 views