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
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30878 views

04:27:20
Kernel Methods
Jan 25, 2013
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15279 views

01:35:21
Channel Coding with LDPC Codes
Jan 25, 2013
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4886 views

05:24:16
Dimensionality Reduction
Jan 25, 2013
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13804 views

38:31
Gaussian Process: Practical Course
Jan 15, 2013
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8955 views

02:26:14
Bayesian Modelling
Jan 15, 2013
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18284 views

05:11:50
Optimization: Theory and Algorithms
Jan 15, 2013
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12534 views

01:16:16
Graphical Models
Jan 15, 2013
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8267 views

01:47:17
Nonparametric Bayesian Modelling
Jan 15, 2013
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8734 views

01:25:50
Graph-based Semi-supervised Learning
Jan 15, 2013
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6203 views

04:41:49
Concentration inequalities in machine learning
Jan 15, 2013
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11741 views

01:27:44
Gaussian Processes
Jan 15, 2013
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14407 views

05:42:27
Diffusions and Geodesic Flows on Manifolds: The Differential Geometry of Markov ...
Jan 15, 2013
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7301 views

52:32
Dirichlet Process: Practical Course
Jan 15, 2013
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11348 views

03:24:27
Introduction to Bayesian Nonparametrics
Jan 15, 2013
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25533 views

01:47:38
Kingman's Coalescent for Hierarchical Representations
Jan 15, 2013
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4227 views

01:34:47
Probabilistic decision-making, data analysis, and discovery in astronomy
Jan 15, 2013
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3908 views