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  2018, Vol. 31 Issue (2): 190-196    DOI: 10.16451/j.cnki.issn1003-6059.201802011
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Regularization Path Algorithm of Multiple Kernel Learning for Solving Large Scale Problems
WANG Mei1,2, LI Dong1, SUN Yingqi1, SONG Kaoping2,3, LIAO Shizhong4
1.School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318
2.Center for Post-Doctoral Studies of Beijing Deweijiaye Science and Technology Ltd, Beijing 100020
3.The Key Laboratory of Enhanced Oil and Gas Recovery of Education Ministry, Northeast Petroleum University, Daqing 163318
4.School of Computer Science and Technology, Tianjin University, Tianjin 300072

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Abstract  

Compared with the traditional single kernel, multiple kernel learning is more flexible and interpretable while dealing with heterogeneous, irregular and non-flat distribution samples. It is difficult for the existing accurate regularization path algorithms to solve large-scale problems. Therefore, an approximation algorithm for multiple kernel learning regularization path is proposed in this paper. The kernel matrix is randomly sampled according to the sampling distribution function, and the corresponding lines are extracted from the Lagrange multiplier vector. Then, the product of matrix is approximately computed, and the efficiency of the regularization path of multiple kernel learning is improved. Finally, the approximation error bounds and the computational complexity of the algorithm are analyzed. Experimental results on standard datasets verify the validity and efficiency of the proposed algorithm.

Key wordsMultiple Kernel Learning      Regularization Path      Matrix Approximation      Monte Carlo Method     
Received: 20 August 2017     
ZTFLH: TP 181  
Fund:

Supported by National Natural Science Foundation of China(No.61502094,51774090), Natural Science Foundation of Heilong-jiang Province(No.F2015020,F2016002,E2016008), Beijing Postdoctoral Research Foundation(No.2015ZZ-120), Chaoyang District Postdoctoral Foundation of Beijing(No.2014ZZ-14), Cultivation Foundation of Northeast Petroleum University(No.XN2014102), Youth Foundation of School of Computer and Information Technology of Northeast Petroleum University

About author:: WANG Mei, Ph.D., associate professor. Her research interests include machine lear-ning, model selection and kernel methods.LI Dong, master student. Her research interests include machine learning.SUN Yingqi, master student. Her research interests include machine learning.SONG Kaoping(Corresponding author), Ph.D., professor. His research interests include oil and gas field development enginee-ring and knowledge engineering.LIAO Shizhong, Ph.D., professor. His research interests include artificial intelligence and theoretical computer science.
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WANG Mei
LI Dong
SUN Yingqi
SONG Kaoping
LIAO Shizhong
Cite this article:   
WANG Mei,LI Dong,SUN Yingqi等. Regularization Path Algorithm of Multiple Kernel Learning for Solving Large Scale Problems[J]. , 2018, 31(2): 190-196.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201802011      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I2/190
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