Location: EU Supported » PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning » Machine Learning Summer School 2004 - Berder Island

Introduction to Kernel Methods

author:Bernhard Schölkopf, Max Planck Institute for Biological Cybernetics, Max Planck Institute
published: Feb. 25, 2007,   recorded: September 2004,   views: 1501
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Slides

Slides
1:36 Introduction to Kernel Methods
8:34 Learning and Similary:Some Informal Thoughts
11:19 Simlary of Inputs
13:34 An Example of a Kernel Algorithm
17:36 An Example of a Kernel Algorithm,ctd.(44)
18:21 An Example of a Kernel Algorithm,
18:31 An Example of a Kernel Algorithm,ctd.(44),
18:59 An Example of a Kernel Algorithm,,
19:26 An Example of a Kernel Algorithm,ctd.(44),,
19:34 An Example of a Kernel Algorithm,,,
36:25 An Example of a Kernel Algorithm,ctd.(44),,,
45:33 An Example of a Kernel Algorithm, ctd.(44).
47:37 Example:All Degree 2 Monominals.
50:13 An Example of a Kernel Algorithm,ctd.
50:14 An Example of a Kernel Algorithm,ctd(44)..
50:15 An Example of a Kernel Algorithm,.,
50:21 An Example of a Kernel Algorithm,ctd.(44),..,
50:22 An Example of a Kernel Algorithm,ctd.,,.
50:23 Example:All Degree 2 Monominals,
50:34 General Product Feature Space,,
51:30 Example:All Degree 2 Monominals,,
51:38 General Product Feature Space,
52:08 The Kernel Trick, N=d=2
52:22 Example:All Degree 2 Monominals,,,
52:28 The Kernel Trick, N=d=2 ,
55:25 The Kernel Trick,II..
55:41 The Kernel Trick,N=d=2,,
55:45 The Kernel Trick,II,
57:27 Mercer\"s Theorem
59:17 The Mercer Feature Map,.
59:33 Mercer\"s Theorem..
59:42 The Mercer Feature Map..
60:33 The Kernel Trick-Summary.,

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Description

The course will cover the basics of Support Vector Machines and related kerne methods: 1. Kernels and Feature Spaces
2. Large Margin Classification
3. Basic Ideas of Learning Theory
4. Support Vector Machines
5. Examples of Other Kernel Algorithms

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