Machine Learning Summer School (MLSS), La Palma 2012
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.
02:13:09
What is Machine Learning?
May 13, 2013 30955 views
04:27:20
Kernel Methods
Jan 25, 2013 15325 views
01:35:21
Channel Coding with LDPC Codes
Jan 25, 2013 4903 views
05:24:16
Dimensionality Reduction
Jan 25, 2013 13858 views
01:16:16
Graphical Models
Jan 15, 2013 8354 views
05:42:27
Diffusions and Geodesic Flows on Manifolds: The Differential Geometry of Markov ...
Jan 15, 2013 7361 views
01:47:17
Nonparametric Bayesian Modelling
Jan 15, 2013 8763 views
01:25:50
Graph-based Semi-supervised Learning
Jan 15, 2013 6225 views
52:32
Dirichlet Process: Practical Course
Jan 15, 2013 11364 views
01:27:44
Gaussian Processes
Jan 15, 2013 14437 views
01:34:47
Probabilistic decision-making, data analysis, and discovery in astronomy
Jan 15, 2013 3929 views
04:41:49
Concentration inequalities in machine learning
Jan 15, 2013 11789 views
03:24:27
Introduction to Bayesian Nonparametrics
Jan 15, 2013 25621 views
05:11:50
Optimization: Theory and Algorithms
Jan 15, 2013 12576 views
01:47:38
Kingman's Coalescent for Hierarchical Representations
Jan 15, 2013 4239 views
38:31
Gaussian Process: Practical Course
Jan 15, 2013 8980 views
02:26:14
Bayesian Modelling
Jan 15, 2013 18324 views
