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Fast kernel ICA using an approximate Newton method

Shen, Hao; Jegelka, Stefanie; Gretton, Arthur


Recent approaches to independent component analysis (ICA) have used kernel independence measures to obtain very good performance, particularly where classical methods experience difficulty (for instance, sources with near-zero kurtosis). We present fast kernel ICA (FastKICA), a novel optimisation technique for one such kernel independence measure, the Hilbert-Schmidt independence criterion (HSIC). Our search procedure uses an approximate Newton method on the special orthogonal group, where we...[Show more]

CollectionsANU Research Publications
Date published: 2007
Type: Conference paper
Source: Proceedings of The 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007)


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