A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface

Yuanqing Li; Huiqi Li; Cuntai Guan; Zhengyang Chin

doi:10.1109/ICASSP.2007.366697

A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface

Yuanqing Li^*, Huiqi Li, Cuntai Guan, Zhengyang Chin

^*Corresponding author for this work

Agency for Science, Technology and Research, Singapore

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

22 Citations (Scopus)

Abstract

In this paper, we analyze the convergence of an iterative self-training semi-supervised support vector machine (SVM) algorithm, which is designed for classification in small training data case. This algorithm converges fast and has low computational burden. Its effectiveness is also demonstrated by our data analysis results. Furthermore, we illustrate that this algorithm can be used to significantly reduce training effort and improve adaptability of a brain computer interface (BCI) system, a P300-based speller.

Original language	English
Title of host publication	2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Pages	I385-I388
DOIs	https://doi.org/10.1109/ICASSP.2007.366697
Publication status	Published - 2007
Externally published	Yes
Event	2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States Duration: 15 Apr 2007 → 20 Apr 2007

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	1
ISSN (Print)	1520-6149

Conference

Conference	2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Country/Territory	United States
City	Honolulu, HI
Period	15/04/07 → 20/04/07

Keywords

Brain computer interface (BCI)
Convergence
P300
Semi-supervised learning
Supporter vector machine (SVM)

Access to Document

10.1109/ICASSP.2007.366697

Cite this

Li, Y., Li, H., Guan, C., & Chin, Z. (2007). A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 (pp. I385-I388). Article 4217097 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 1). https://doi.org/10.1109/ICASSP.2007.366697

Li, Yuanqing ; Li, Huiqi ; Guan, Cuntai et al. / A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface. 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07. 2007. pp. I385-I388 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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title = "A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface",

abstract = "In this paper, we analyze the convergence of an iterative self-training semi-supervised support vector machine (SVM) algorithm, which is designed for classification in small training data case. This algorithm converges fast and has low computational burden. Its effectiveness is also demonstrated by our data analysis results. Furthermore, we illustrate that this algorithm can be used to significantly reduce training effort and improve adaptability of a brain computer interface (BCI) system, a P300-based speller.",

keywords = "Brain computer interface (BCI), Convergence, P300, Semi-supervised learning, Supporter vector machine (SVM)",

author = "Yuanqing Li and Huiqi Li and Cuntai Guan and Zhengyang Chin",

year = "2007",

doi = "10.1109/ICASSP.2007.366697",

language = "English",

isbn = "1424407281",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

pages = "I385--I388",

booktitle = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07",

note = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 ; Conference date: 15-04-2007 Through 20-04-2007",

}

Li, Y, Li, H, Guan, C & Chin, Z 2007, A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface. in 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07., 4217097, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 1, pp. I385-I388, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, Honolulu, HI, United States, 15/04/07. https://doi.org/10.1109/ICASSP.2007.366697

A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface. / Li, Yuanqing; Li, Huiqi; Guan, Cuntai et al.
2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07. 2007. p. I385-I388 4217097 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 1).

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

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AB - In this paper, we analyze the convergence of an iterative self-training semi-supervised support vector machine (SVM) algorithm, which is designed for classification in small training data case. This algorithm converges fast and has low computational burden. Its effectiveness is also demonstrated by our data analysis results. Furthermore, we illustrate that this algorithm can be used to significantly reduce training effort and improve adaptability of a brain computer interface (BCI) system, a P300-based speller.

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KW - Convergence

KW - P300

KW - Semi-supervised learning

KW - Supporter vector machine (SVM)

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Li Y, Li H, Guan C, Chin Z. A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07. 2007. p. I385-I388. 4217097. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2007.366697

A self-training semi-supervised support vector machine algorithm and its applications in brain computer interface

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