Sparse approximation based on wavelet kernel support vector machines

Dong Kai Yang; Yu Bing Tong; Qi Shan Zhang

doi:10.1109/ICMLC.2005.1527683

Sparse approximation based on wavelet kernel support vector machines

Dong Kai Yang^*
, Yu Bing Tong
, Qi Shan Zhang

^*Corresponding author for this work

School of Electronic and Information Engineering

Beihang University

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

Abstract

For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel support vector machines, which can converge to minimum error with better sparsity. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.

Original language	English
Title of host publication	2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Publisher	IEEE Computer Society
Pages	4249-4253
Number of pages	5
ISBN (Electronic)	0780390911
ISBN (Print)	078039092X, 9780780390928
DOIs	https://doi.org/10.1109/ICMLC.2005.1527683
State	Published - 2005
Event	4th International Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China Duration: 18 Aug 2005 → 21 Aug 2005

Publication series

Name	2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Volume	7

Conference

Conference	4th International Conference on Machine Learning and Cybernetics, ICMLC 2005
Country/Territory	China
City	Guangzhou
Period	18/08/05 → 21/08/05

Keywords

Sparse Approximation
Support Vector Machine
Wavelet Kernel Function

Access to Document

10.1109/ICMLC.2005.1527683

Cite this

Yang, D. K., Tong, Y. B., & Zhang, Q. S. (2005). Sparse approximation based on wavelet kernel support vector machines. In 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005 (pp. 4249-4253). (2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005; Vol. 7). IEEE Computer Society. https://doi.org/10.1109/ICMLC.2005.1527683

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title = "Sparse approximation based on wavelet kernel support vector machines",

abstract = "For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel support vector machines, which can converge to minimum error with better sparsity. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.",

keywords = "Sparse Approximation, Support Vector Machine, Wavelet Kernel Function",

author = "Yang, \{Dong Kai\} and Tong, \{Yu Bing\} and Zhang, \{Qi Shan\}",

year = "2005",

doi = "10.1109/ICMLC.2005.1527683",

language = "英语",

isbn = "078039092X",

series = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",

publisher = "IEEE Computer Society",

pages = "4249--4253",

booktitle = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",

address = "美国",

note = "4th International Conference on Machine Learning and Cybernetics, ICMLC 2005 ; Conference date: 18-08-2005 Through 21-08-2005",

}

Yang, DK, Tong, YB & Zhang, QS 2005, Sparse approximation based on wavelet kernel support vector machines. in 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005. 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005, vol. 7, IEEE Computer Society, pp. 4249-4253, 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, Guangzhou, China, 18/08/05. https://doi.org/10.1109/ICMLC.2005.1527683

Sparse approximation based on wavelet kernel support vector machines. / Yang, Dong Kai; Tong, Yu Bing; Zhang, Qi Shan.
2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005. IEEE Computer Society, 2005. p. 4249-4253 (2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005; Vol. 7).

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

TY - GEN

T1 - Sparse approximation based on wavelet kernel support vector machines

AU - Yang, Dong Kai

AU - Tong, Yu Bing

AU - Zhang, Qi Shan

PY - 2005

Y1 - 2005

N2 - For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel support vector machines, which can converge to minimum error with better sparsity. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.

AB - For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel support vector machines, which can converge to minimum error with better sparsity. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.

KW - Sparse Approximation

KW - Support Vector Machine

KW - Wavelet Kernel Function

UR - https://www.scopus.com/pages/publications/28444461493

U2 - 10.1109/ICMLC.2005.1527683

DO - 10.1109/ICMLC.2005.1527683

M3 - 会议稿件

AN - SCOPUS:28444461493

SN - 078039092X

SN - 9780780390928

T3 - 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

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EP - 4253

BT - 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

PB - IEEE Computer Society

T2 - 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005

Y2 - 18 August 2005 through 21 August 2005

ER -

Sparse approximation based on wavelet kernel support vector machines

Abstract

Publication series

Conference

Keywords

Access to Document

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