NIPS
2007
14 years 2 months ago
2007
Although kernel measures of independence have been widely applied in machine learning (notably in kernel ICA), there is as yet no method to determine whether they have detected st...
IDEAL
2009
Springer
14 years 7 months ago
2009
Springer
We propose a novel, supervised feature extraction procedure, based on an unbiased estimator of the Hilbert-Schmidt independence criterion (HSIC). The proposed procedure can be dire...
ICML
2007
IEEE
15 years 1 months ago
2007
IEEE
We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The ...
ICML
2007
IEEE
15 years 1 months ago
2007
IEEE
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...