Machine Learning Summer School 2007 - Tuebingen

Kernel Methods for Dependence and Causality

author: Kenji Fukumizu, Institute of Statistical Mathematics

Categories

Top: Computer Science: Machine Learning: Kernel Methods

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*Slides*
0:00	III. Covariance on RKHS
0:00	III. Covariance on RKHS
0:18	Two Views on Kernel Methods
2:16	Covariance on RKHS
4:56	Cross-covariance operator
7:33	Intuition
11:34	Addendum on “operator”
12:10	Characterization of Independence
17:29	Measures for Dependence
19:19	Norms of operators
22:57	Empirical Estimation
25:12	Empirical cross-covariance operator
26:08	COCO Revisited
27:07	HSIC Revisited
28:28	Application of HSIC to ICA
31:02	ICA with HSIC
32:15	Experiments (speech signal)
35:15	Normalized Covariance
35:54	HSIC Revisited
36:28	Nonlinear dependence

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