Hierarchical model selection for NGnet based on variational Bayes inference

Junichiro Yoshimoto; Shin Ishii; Masa Aki Sato

doi:10.1007/3-540-46084-5_108

Hierarchical model selection for NGnet based on variational Bayes inference

Junichiro Yoshimoto, Shin Ishii, Masa Aki Sato

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This article presents a variational Bayes inference for normalized Gaussian network, which is a kind of mixture models of local experts. In order to search for the optimal model structure, we develop a hierarchical model selection method. The performance of our method is evaluated by using function approximation and nonlinear dynamical system identification problems. Our method achieved better performance than existing methods.

Original language	English
Title of host publication	Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings
Editors	Jose R. Dorronsoro, Jose R. Dorronsoro
Publisher	Springer Verlag
Pages	661-666
Number of pages	6
ISBN (Print)	9783540440741
DOIs	https://doi.org/10.1007/3-540-46084-5_108
Publication status	Published - 2002
Externally published	Yes
Event	2002 International Conference on Artificial Neural Networks, ICANN 2002 - Madrid, Spain Duration: 28-08-2002 → 30-08-2002

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2415 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2002 International Conference on Artificial Neural Networks, ICANN 2002
Country/Territory	Spain
City	Madrid
Period	28-08-02 → 30-08-02

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/3-540-46084-5_108

Cite this

Yoshimoto, J., Ishii, S., & Sato, M. A. (2002). Hierarchical model selection for NGnet based on variational Bayes inference. In J. R. Dorronsoro, & J. R. Dorronsoro (Eds.), Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings (pp. 661-666). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2415 LNCS). Springer Verlag. https://doi.org/10.1007/3-540-46084-5_108

Yoshimoto, Junichiro ; Ishii, Shin ; Sato, Masa Aki. / Hierarchical model selection for NGnet based on variational Bayes inference. Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings. editor / Jose R. Dorronsoro ; Jose R. Dorronsoro. Springer Verlag, 2002. pp. 661-666 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{e1a6dc9b592d464ca10b2ed8df11c3c6,

title = "Hierarchical model selection for NGnet based on variational Bayes inference",

abstract = "This article presents a variational Bayes inference for normalized Gaussian network, which is a kind of mixture models of local experts. In order to search for the optimal model structure, we develop a hierarchical model selection method. The performance of our method is evaluated by using function approximation and nonlinear dynamical system identification problems. Our method achieved better performance than existing methods.",

author = "Junichiro Yoshimoto and Shin Ishii and Sato, {Masa Aki}",

year = "2002",

doi = "10.1007/3-540-46084-5_108",

language = "English",

isbn = "9783540440741",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "661--666",

editor = "Dorronsoro, {Jose R.} and Dorronsoro, {Jose R.}",

booktitle = "Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings",

address = "Germany",

note = "2002 International Conference on Artificial Neural Networks, ICANN 2002 ; Conference date: 28-08-2002 Through 30-08-2002",

}

Yoshimoto, J, Ishii, S & Sato, MA 2002, Hierarchical model selection for NGnet based on variational Bayes inference. in JR Dorronsoro & JR Dorronsoro (eds), Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2415 LNCS, Springer Verlag, pp. 661-666, 2002 International Conference on Artificial Neural Networks, ICANN 2002, Madrid, Spain, 28-08-02. https://doi.org/10.1007/3-540-46084-5_108

Hierarchical model selection for NGnet based on variational Bayes inference. / Yoshimoto, Junichiro; Ishii, Shin; Sato, Masa Aki.
Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings. ed. / Jose R. Dorronsoro; Jose R. Dorronsoro. Springer Verlag, 2002. p. 661-666 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2415 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Hierarchical model selection for NGnet based on variational Bayes inference

AU - Yoshimoto, Junichiro

AU - Ishii, Shin

AU - Sato, Masa Aki

PY - 2002

Y1 - 2002

N2 - This article presents a variational Bayes inference for normalized Gaussian network, which is a kind of mixture models of local experts. In order to search for the optimal model structure, we develop a hierarchical model selection method. The performance of our method is evaluated by using function approximation and nonlinear dynamical system identification problems. Our method achieved better performance than existing methods.

AB - This article presents a variational Bayes inference for normalized Gaussian network, which is a kind of mixture models of local experts. In order to search for the optimal model structure, we develop a hierarchical model selection method. The performance of our method is evaluated by using function approximation and nonlinear dynamical system identification problems. Our method achieved better performance than existing methods.

UR - http://www.scopus.com/inward/record.url?scp=84902155301&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84902155301&partnerID=8YFLogxK

U2 - 10.1007/3-540-46084-5_108

DO - 10.1007/3-540-46084-5_108

M3 - Conference contribution

AN - SCOPUS:84902155301

SN - 9783540440741

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 661

EP - 666

BT - Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings

A2 - Dorronsoro, Jose R.

PB - Springer Verlag

T2 - 2002 International Conference on Artificial Neural Networks, ICANN 2002

Y2 - 28 August 2002 through 30 August 2002

ER -

Yoshimoto J, Ishii S, Sato MA. Hierarchical model selection for NGnet based on variational Bayes inference. In Dorronsoro JR, Dorronsoro JR, editors, Artificial Neural Networks, ICANN 2002 - International Conference, Proceedings. Springer Verlag. 2002. p. 661-666. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-46084-5_108

Hierarchical model selection for NGnet based on variational Bayes inference

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this