Skip navigation
Skip navigation

Fast kernel ICA using an approximate Newton method

Shen, Hao; Jegelka, Stefanie; Gretton, Arthur

Description

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
URI: http://hdl.handle.net/1885/38791
Source: Proceedings of The 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007)

Download

File Description SizeFormat Image
01_Shen_Fast_kernel_ICA_using_an_2007.pdf370.55 kBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  12 November 2018/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator