New paper: Relative Newton Method for Quasi-ML Blind Source Separation
Michael Zibulevsky
mzib at ee.technion.ac.il
Fri Oct 4 09:45:53 EDT 2002
Announcing a paper ...
Title: Relative Newton Method for Quasi-ML Blind Source Separation
Author: Michael Zibulevsky
ABSTRACT:
Presented relative Newton method for quasi-maximum likelihood blind source
separation significantly outperforms natural gradient descent in batch mode.
The structure of the corresponding Hessian matrix allows its fast inversion
without assembling. Experiments with sparsely representable signals and images
demonstrate super-efficient separation.
URL of gzipped ps file:
http://ie.technion.ac.il/~mcib/newt_ica_jmlr1.ps.gz
Contact: mzib at ee.technion.ac.il
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Michael Zibulevsky, Ph.D. Email: mzib at ee.technion.ac.il
Faculty of Electrical Engineering Phone: 972-4-829-4724
Technion - Israel Institute of Technology 972-4-832-3885
Haifa 32000, Israel Cell: 972-55-968297
http://ie.technion.ac.il/~mcib/ Fax: 972-4-829-4799
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