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

Related categories

Uploaded videos:

video-img
02:51:04

Introduction To Bayesian Inference

Christopher Bishop

Nov 02, 2009

 · 

369806 Views

Tutorial
video-img
02:36:18

Graphical Models

Zoubin Ghahramani

Nov 02, 2009

 · 

60369 Views

Tutorial
video-img
02:27:57

Markov Chain Monte Carlo

Iain Murray

Nov 02, 2009

 · 

236686 Views

Tutorial
video-img
03:02:15

Information Theory

David MacKay

Nov 02, 2009

 · 

70056 Views

Tutorial
video-img
02:39:22

Kernel Methods

Bernhard Schölkopf

Nov 02, 2009

 · 

17888 Views

Tutorial
video-img
03:07:21

Approximate Inference

Tom Minka

Nov 02, 2009

 · 

60870 Views

Tutorial
video-img
02:57:01

Topic Models

David Blei

Nov 02, 2009

 · 

312466 Views

Tutorial
video-img
02:57:21

Gaussian Processes

Carl Edward Rasmussen

Nov 02, 2009

 · 

58996 Views

Tutorial
video-img
02:52:49

Convex Optimization

Lieven Vandenberghe

Nov 02, 2009

 · 

15547 Views

Tutorial
video-img
02:44:43

Learning Theory

John Shawe-Taylor

Nov 02, 2009

 · 

13594 Views

Tutorial
video-img
02:53:15

Computer Vision

Andrew Blake

Nov 02, 2009

 · 

17406 Views

Tutorial
video-img
03:02:29

Nonparametric Bayesian Models

Yee Whye Teh

Nov 02, 2009

 · 

54008 Views

Tutorial
video-img
03:13:48

Machine Learning and Cognitive Science

Joshua B. Tenenbaum

Nov 02, 2009

 · 

12187 Views

Tutorial
video-img
02:56:42

Reinforcement Learning

Michael Littman

Nov 02, 2009

 · 

18038 Views

Tutorial
video-img
02:46:58

Foundations of Nonparametric Bayesian Methods

Peter Orbanz

Nov 02, 2009

 · 

39724 Views

Tutorial
video-img
02:55:43

Deep Belief Networks

Geoffrey E. Hinton

Nov 02, 2009

 · 

103567 Views

Tutorial
video-img
02:07:58

Particle Filters

Simon Godsill

Nov 02, 2009

 · 

54677 Views

Tutorial
video-img
02:57:01

Causality

Phil Dawid

Nov 02, 2009

 · 

12438 Views

Tutorial
video-img
02:53:44

Information Retrieval

Thomas Hofmann

Nov 02, 2009

 · 

9855 Views

Tutorial
video-img
02:57:16

Bayesian or Frequentist, Which Are You?

Michael I. Jordan

Nov 02, 2009

 · 

108152 Views

Tutorial