Machine Learning Summer School (MLSS), La Palma 2012
17 Lectures · 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.
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Uploaded videos:
04:27:20
Kernel Methods
Jan 25, 2013
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15219 Views
05:24:16
Dimensionality Reduction
Jan 25, 2013
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13702 Views
02:13:09
What is Machine Learning?
May 13, 2013
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30768 Views
05:42:27
Diffusions and Geodesic Flows on Manifolds: The Differential Geometry of Markov ...
Jan 15, 2013
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7236 Views
05:11:50
Optimization: Theory and Algorithms
Jan 15, 2013
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12473 Views
01:47:38
Kingman's Coalescent for Hierarchical Representations
Jan 15, 2013
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4197 Views
01:35:21
Channel Coding with LDPC Codes
Jan 25, 2013
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4855 Views
02:26:14
Bayesian Modelling
Jan 15, 2013
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18218 Views
03:24:27
Introduction to Bayesian Nonparametrics
Jan 15, 2013
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25369 Views
52:32
Dirichlet Process: Practical Course
Jan 15, 2013
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11328 Views
01:16:16
Graphical Models
Jan 15, 2013
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8177 Views
01:27:44
Gaussian Processes
Jan 15, 2013
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14368 Views
38:31
Gaussian Process: Practical Course
Jan 15, 2013
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8934 Views
04:41:49
Concentration inequalities in machine learning
Jan 15, 2013
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11685 Views
01:25:50
Graph-based Semi-supervised Learning
Jan 15, 2013
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6166 Views
01:47:17
Nonparametric Bayesian Modelling
Jan 15, 2013
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8696 Views
01:34:47
Probabilistic decision-making, data analysis, and discovery in astronomy
Jan 15, 2013
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3856 Views