About
Machine Learning is a foundational discipline of the Information Sciences. It combines theory from areas as diverse as Statistics, Mathematics, Engineering, and Information Technology with many practical and relevant real life applications. The aim of the summer school is to cover the entire spectrum from theory to practice. It is mainly targeted at research students, academics, and IT professionals from all over the world. The program will feature introductory courses at the beginning to provide basic working knowledge of Machine Learning. Building on this introductory material, advanced topics will be covered progressively over the duration of the school. Subjects will be covered both in lectures (4-6 per topic) and in practical courses (where students will have the chance to implement methods for themselves); and are taught by world experts in their fields.\
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Uploaded videos:
Opening and Closing
Opening of the 9th Machine Learning Summer School
Aug 26, 2007
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7546 Views
Closing remarks
Sep 02, 2007
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4544 Views
Lectures
Graphical models
Aug 25, 2007
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95162 Views
Introduction to kernel methods
Aug 20, 2007
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50755 Views
Introduction to bioinformatics
Aug 20, 2007
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51226 Views
Bayesian inference and Gaussian processes
Aug 20, 2007
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78134 Views
Kernel Methods for Dependence and Causality
Aug 26, 2007
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8110 Views
Convex Optimization
Aug 26, 2007
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41311 Views
Statistical learning theory
Aug 27, 2007
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13927 Views
Dirichlet Processes: Tutorial and Practical Course
Aug 27, 2007
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140417 Views
Topics in image and video processing
Aug 27, 2007
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36680 Views
Online Learning
Aug 29, 2007
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11202 Views
Machine learning and finance
Aug 29, 2007
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22587 Views
Sequential Monte Carlo methods
Aug 30, 2007
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35650 Views
Sequential Monte Carlo methods continued
Oct 30, 2007
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7939 Views
Interviews
Interview about past, present, future of MLSS
Sep 04, 2007
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7719 Views
A discussion about ML
Sep 04, 2007
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15487 Views
Leisure time - music events during MLSS 2007
Students performing "Easy" on the last day of the MLSS
Sep 01, 2007
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6924 Views