Machine Learning Summer School (MLSS), Cambridge 2009

Machine Learning Summer School (MLSS), Cambridge 2009

20 Lectures · Aug 27, 2009

About

The 13th Machine Learning Summer School was held in Cambridge, UK. This year's edition was organized by the University of Cambridge, Microsoft Research and PASCAL. The school offered an overview of basic and advanced topics in machine learning through theoretical and practical lectures given by leading researchers in the field. We hope to attract international students, young researchers and industry practitioners with a keen interest in machine learning and a strong mathematical background.


The Summer school homepage can be found at http://mlg.eng.cam.ac.uk/mlss09/index.html

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Uploaded videos:

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02:51:04

Introduction To Bayesian Inference

Christopher Bishop

Nov 02, 2009

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369888 Views

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02:36:18

Graphical Models

Zoubin Ghahramani

Nov 02, 2009

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60393 Views

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02:27:57

Markov Chain Monte Carlo

Iain Murray

Nov 02, 2009

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236945 Views

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03:02:15

Information Theory

David MacKay

Nov 02, 2009

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70074 Views

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02:39:22

Kernel Methods

Bernhard Schölkopf

Nov 02, 2009

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17896 Views

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03:07:21

Approximate Inference

Tom Minka

Nov 02, 2009

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60907 Views

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02:57:01

Topic Models

David Blei

Nov 02, 2009

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312625 Views

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02:57:21

Gaussian Processes

Carl Edward Rasmussen

Nov 02, 2009

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59060 Views

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02:52:49

Convex Optimization

Lieven Vandenberghe

Nov 02, 2009

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15558 Views

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02:44:43

Learning Theory

John Shawe-Taylor

Nov 02, 2009

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13598 Views

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02:53:15

Computer Vision

Andrew Blake

Nov 02, 2009

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17409 Views

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03:02:29

Nonparametric Bayesian Models

Yee Whye Teh

Nov 02, 2009

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54031 Views

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03:13:48

Machine Learning and Cognitive Science

Joshua B. Tenenbaum

Nov 02, 2009

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12202 Views

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02:56:42

Reinforcement Learning

Michael Littman

Nov 02, 2009

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18048 Views

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02:46:58

Foundations of Nonparametric Bayesian Methods

Peter Orbanz

Nov 02, 2009

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39743 Views

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02:55:43

Deep Belief Networks

Geoffrey E. Hinton

Nov 02, 2009

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103622 Views

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02:07:58

Particle Filters

Simon Godsill

Nov 02, 2009

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54691 Views

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02:57:01

Causality

Phil Dawid

Nov 02, 2009

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12538 Views

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02:53:44

Information Retrieval

Thomas Hofmann

Nov 02, 2009

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9865 Views

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02:57:16

Bayesian or Frequentist, Which Are You?

Michael I. Jordan

Nov 02, 2009

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108289 Views

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