About
The school addresses the following topics: Learning Theory, Kernel Methods, Bayesian Machine learning, Monte Carlo Methods , Bayesian Nonparametrics, Optimization, Graphical Models, Information theory and Dimensionality Reduction.
Detailed information can be found here.
Videos
02:13:09
What is Machine Learning?
May 13, 2013 30930 views
01:35:21
Channel Coding with LDPC Codes
Jan 25, 2013 4897 views
05:24:16
Dimensionality Reduction
Jan 25, 2013 13839 views
04:27:20
Kernel Methods
Jan 25, 2013 15304 views
02:26:14
Bayesian Modelling
Jan 15, 2013 18311 views
01:16:16
Graphical Models
Jan 15, 2013 8328 views
01:47:17
Nonparametric Bayesian Modelling
Jan 15, 2013 8752 views
52:32
Dirichlet Process: Practical Course
Jan 15, 2013 11362 views
05:11:50
Optimization: Theory and Algorithms
Jan 15, 2013 12560 views
04:41:49
Concentration inequalities in machine learning
Jan 15, 2013 11765 views
03:24:27
Introduction to Bayesian Nonparametrics
Jan 15, 2013 25588 views
01:47:38
Kingman's Coalescent for Hierarchical Representations
Jan 15, 2013 4233 views
05:42:27
Diffusions and Geodesic Flows on Manifolds: The Differential Geometry of Markov ...
Jan 15, 2013 7322 views
01:25:50
Graph-based Semi-supervised Learning
Jan 15, 2013 6215 views
01:34:47
Probabilistic decision-making, data analysis, and discovery in astronomy
Jan 15, 2013 3923 views
01:27:44
Gaussian Processes
Jan 15, 2013 14423 views
38:31
Gaussian Process: Practical Course
Jan 15, 2013 8974 views
