Beyond Pham's algorithm for joint diagonalization

Abstract : The approximate joint diagonalization of a set of matrices consists in finding a basis in which these matrices are as diagonal as possible. This problem naturally appears in several statistical learning tasks such as blind signal separation. We consider the diagonalization criterion studied in a seminal paper by Pham (2001), and propose a new quasi-Newton method for its optimization. Through numerical experiments on simulated and real datasets, we show that the proposed method outper-forms Pham's algorithm. An open source Python package is released.
Type de document :
Pré-publication, Document de travail
2018
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https://hal.archives-ouvertes.fr/hal-01936887
Contributeur : Pierre Ablin <>
Soumis le : mardi 27 novembre 2018 - 16:52:27
Dernière modification le : vendredi 30 novembre 2018 - 01:36:36

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  • HAL Id : hal-01936887, version 1
  • ARXIV : 1811.11433

Citation

Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort. Beyond Pham's algorithm for joint diagonalization. 2018. 〈hal-01936887〉

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