Independent process analysis without a priori dimensional information

Barnabás Póczos, Zoltán Szabó, Melinda Kiszlinger, A. Lőrincz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Recently, several algorithms have been proposed for independent subspace analysis where hidden variables are i.i.d. processes. We show that these methods can be extended to certain AR, MA, ARMA and ARIMA tasks. Central to our paper is that we introduce a cascade of algorithms, which aims to solve these tasks without previous knowledge about the number and the dimensions of the hidden processes. Our claim is supported by numerical simulations. As an illustrative application where the dimensions of the hidden variables are unknown, we search for subspaces of facial components.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages252-259
Number of pages8
Volume4666 LNCS
Publication statusPublished - 2007
Event7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007 - London, United Kingdom
Duration: Sep 9 2007Sep 12 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4666 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007
CountryUnited Kingdom
CityLondon
Period9/9/079/12/07

Fingerprint

Hidden Variables
Subspace
ARIMA
Autoregressive Moving Average
Cascade
Unknown
Numerical Simulation
Computer simulation
Knowledge

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Póczos, B., Szabó, Z., Kiszlinger, M., & Lőrincz, A. (2007). Independent process analysis without a priori dimensional information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4666 LNCS, pp. 252-259). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4666 LNCS).

Independent process analysis without a priori dimensional information. / Póczos, Barnabás; Szabó, Zoltán; Kiszlinger, Melinda; Lőrincz, A.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4666 LNCS 2007. p. 252-259 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4666 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Póczos, B, Szabó, Z, Kiszlinger, M & Lőrincz, A 2007, Independent process analysis without a priori dimensional information. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4666 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4666 LNCS, pp. 252-259, 7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007, London, United Kingdom, 9/9/07.
Póczos B, Szabó Z, Kiszlinger M, Lőrincz A. Independent process analysis without a priori dimensional information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4666 LNCS. 2007. p. 252-259. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Póczos, Barnabás ; Szabó, Zoltán ; Kiszlinger, Melinda ; Lőrincz, A. / Independent process analysis without a priori dimensional information. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4666 LNCS 2007. pp. 252-259 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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