Machine Learning Summer School (MLSS), La Palma 2012
17 Videos · Apr 11, 2012
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
05:42:27
Diffusions and Geodesic Flows on Manifolds: The Differential Geometry of Markov ...
Jan 15, 2013
·
7256 views
52:32
Dirichlet Process: Practical Course
Jan 15, 2013
·
11337 views
05:24:16
Dimensionality Reduction
Jan 25, 2013
·
13731 views
05:11:50
Optimization: Theory and Algorithms
Jan 15, 2013
·
12504 views
01:27:44
Gaussian Processes
Jan 15, 2013
·
14390 views
01:25:50
Graph-based Semi-supervised Learning
Jan 15, 2013
·
6184 views
01:35:21
Channel Coding with LDPC Codes
Jan 25, 2013
·
4869 views
01:47:38
Kingman's Coalescent for Hierarchical Representations
Jan 15, 2013
·
4210 views
02:13:09
What is Machine Learning?
May 13, 2013
·
30793 views
04:41:49
Concentration inequalities in machine learning
Jan 15, 2013
·
11709 views
04:27:20
Kernel Methods
Jan 25, 2013
·
15246 views
01:47:17
Nonparametric Bayesian Modelling
Jan 15, 2013
·
8711 views
01:16:16
Graphical Models
Jan 15, 2013
·
8204 views
02:26:14
Bayesian Modelling
Jan 15, 2013
·
18239 views
38:31
Gaussian Process: Practical Course
Jan 15, 2013
·
8944 views
03:24:27
Introduction to Bayesian Nonparametrics
Jan 15, 2013
·
25444 views
01:34:47
Probabilistic decision-making, data analysis, and discovery in astronomy
Jan 15, 2013
·
3867 views