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.
Related categories
Uploaded videos:
04:27:20
Kernel Methods
Jan 25, 2013
·
15220 Views
05:24:16
Dimensionality Reduction
Jan 25, 2013
·
13701 Views
02:13:09
What is Machine Learning?
May 13, 2013
·
30767 Views
05:42:27
Diffusions and Geodesic Flows on Manifolds: The Differential Geometry of Markov ...
Jan 15, 2013
·
7236 Views
05:11:50
Optimization: Theory and Algorithms
Jan 15, 2013
·
12473 Views
01:47:38
Kingman's Coalescent for Hierarchical Representations
Jan 15, 2013
·
4197 Views
01:35:21
Channel Coding with LDPC Codes
Jan 25, 2013
·
4855 Views
02:26:14
Bayesian Modelling
Jan 15, 2013
·
18218 Views
03:24:27
Introduction to Bayesian Nonparametrics
Jan 15, 2013
·
25367 Views
52:32
Dirichlet Process: Practical Course
Jan 15, 2013
·
11327 Views
01:16:16
Graphical Models
Jan 15, 2013
·
8177 Views
01:27:44
Gaussian Processes
Jan 15, 2013
·
14367 Views
38:31
Gaussian Process: Practical Course
Jan 15, 2013
·
8934 Views
04:41:49
Concentration inequalities in machine learning
Jan 15, 2013
·
11685 Views
01:25:50
Graph-based Semi-supervised Learning
Jan 15, 2013
·
6164 Views
01:47:17
Nonparametric Bayesian Modelling
Jan 15, 2013
·
8696 Views
01:34:47
Probabilistic decision-making, data analysis, and discovery in astronomy
Jan 15, 2013
·
3856 Views