An online transfer learning RBF neural network for cross domain data classification

Shing Chiang Tan; Chee Peng Lim; Manjeevan Seera

doi:10.3233/978-1-61499-405-3-210

An online transfer learning RBF neural network for cross domain data classification

Shing Chiang Tan, Chee Peng Lim, Manjeevan Seera

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

Abstract

In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks.

Original language	English
Title of host publication	Smart Digital Futures 2014
Publisher	IOS Press
Pages	210-218
Number of pages	9
ISBN (Print)	9781614994046
DOIs	https://doi.org/10.3233/978-1-61499-405-3-210
Publication status	Published - 2014
Externally published	Yes
Event	KES International Conference on Intelligent Decision Technologies 2014 - Chania, Greece Duration: 18 Jun 2014 → 20 Jun 2014 Conference number: 6th

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	262
ISSN (Print)	0922-6389

Conference

Conference	KES International Conference on Intelligent Decision Technologies 2014
Abbreviated title	KES IDT 2014
Country/Territory	Greece
City	Chania
Period	18/06/14 → 20/06/14

Keywords

classification
online learning
radial basis function network
Transfer learning

Access to Document

10.3233/978-1-61499-405-3-210

Cite this

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title = "An online transfer learning RBF neural network for cross domain data classification",

abstract = "In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks.",

keywords = "classification, online learning, radial basis function network, Transfer learning",

author = "Tan, \{Shing Chiang\} and Lim, \{Chee Peng\} and Manjeevan Seera",

note = "Copyright: Copyright 2014 Elsevier B.V., All rights reserved.; KES International Conference on Intelligent Decision Technologies 2014, KES IDT 2014 ; Conference date: 18-06-2014 Through 20-06-2014",

year = "2014",

doi = "10.3233/978-1-61499-405-3-210",

language = "English",

isbn = "9781614994046",

series = "Frontiers in Artificial Intelligence and Applications",

publisher = "IOS Press",

pages = "210--218",

booktitle = "Smart Digital Futures 2014",

address = "Netherlands",

}

Tan, SC, Lim, CP & Seera, M 2014, An online transfer learning RBF neural network for cross domain data classification. in Smart Digital Futures 2014. Frontiers in Artificial Intelligence and Applications, vol. 262, IOS Press, pp. 210-218, KES International Conference on Intelligent Decision Technologies 2014, Chania, Greece, 18/06/14. https://doi.org/10.3233/978-1-61499-405-3-210

An online transfer learning RBF neural network for cross domain data classification. / Tan, Shing Chiang; Lim, Chee Peng; Seera, Manjeevan.
Smart Digital Futures 2014. IOS Press, 2014. p. 210-218 (Frontiers in Artificial Intelligence and Applications; Vol. 262).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

TY - GEN

T1 - An online transfer learning RBF neural network for cross domain data classification

AU - Tan, Shing Chiang

AU - Lim, Chee Peng

AU - Seera, Manjeevan

N1 - Conference code: 6th

PY - 2014

Y1 - 2014

N2 - In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks.

AB - In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks.

KW - classification

KW - online learning

KW - radial basis function network

KW - Transfer learning

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DO - 10.3233/978-1-61499-405-3-210

M3 - Conference Paper

AN - SCOPUS:84902340064

SN - 9781614994046

T3 - Frontiers in Artificial Intelligence and Applications

SP - 210

EP - 218

BT - Smart Digital Futures 2014

PB - IOS Press

T2 - KES International Conference on Intelligent Decision Technologies 2014

Y2 - 18 June 2014 through 20 June 2014

ER -

An online transfer learning RBF neural network for cross domain data classification

Abstract

Publication series

Conference

Keywords

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