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  Correspondence

  • Name:   Yuan-Hai Shao
  • E-mail:   shaoyuanhai21@163.com
  • Phone:   (+86)0571-87313551(O)
  • Address:   Zhijiang College, Zhejiang University of Technology, Hangzhou 310024, China

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      Biography


         Yuan-Hai Shao received his B.S. degree in information and computing science in College of Mathematics from Jilin University, the master*s degree in applied mathematics, and Ph.D. degree in operations research and management in College of Science from China Agricultural University, China, in 2006, 2008, and 2011, respectively. Currently, he is an Associate Professor at the Zhijiang College, Zhejiang University of Technology. His research interests include optimization methods, machine learning, and data mining. He has published over 50 refereed papers on these areas.

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      Research Interests

  • Optimization Theory and Application

         Sparse Optimization

         Mathematical analysis of SVM

         SVM solving optimization problems

         Linear Programming and Combinatorics

  • ML/DM topics

         Supervised and Unsupervised learning

         Multi-instance learning

         Semi-supervised and active learning

         Cost-sensitive and class-imbalance learning

         Dimensionality reduction and feature selection

  • Applications

         Image classification and face recognition

         Stock prediction

         Text Mining

         Bioinformatics

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      Academic Activities

  • Activities in Academic Conferences

         2013 and 2014 International Conference on Information Technology and Quantitative Management, Workshop 12, Program Committee (PC) Member

         2013 The International Conference on Computational Science, Workshop 10, Reviewer

         2013 The IEEE International Conference on Data Mining, Workshop 8, Program Committee (PC) Member

  • Reviewers of the following journals

         IEEE Transactions on Neural Networks and Learning Systems

         Int. Journal of Pattern Recognition and Artificial Intelligence

         Knowledge and Information Systems

         Knowledge-Based Systems

         Computational Statistics & Data Analysis

         Neural Computing and Applications

         Optimization

         Applied Mathematics and Computation

         Neurocomputing

         Neural Networks

         Applied Intelligence

         IEEE Transactions on Fuzzy Systems

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    Selected Publications


    [
    Citations at Google Scholar ]
  • Yuan-Hai Shao, Xiang-Yu Hua, Li-Ming Liu, Zhi-Min Yang, Nai-Yang Deng*. Combined outputs framework for twin support vector machines. Applied Intelligence , 2015, inpress.
  • Chun-Na Li, Yuan-Hai Shao*, Nai-Yang Deng. Robust L1-norm two-dimensional linear discriminant analysis. Neural Networks , 2015, 10.1016/j.neunet.2015.01.003. [Code].
  • Yuan-Hai Shao, Wei-Jie Chen, Zhen Wang, Chun-Na Li, Nai-Yang Deng*. Weighted linear loss twin support vector machine for large-scale classification. Knowledge-Based Systems, 73: 276-288 (2015)[Code].
  • Zhi-Min Yang, Yan-Ru Guo*, Chun-Na Li, Yuan-Hai Shao. Local k-proximal plane clustering. Neural Computing and Applications, 2015, 26(1): 199-211 [Code].
  • Yuan-Hai Shao, Nai-Yang Deng*. The Equivalence between Principal Component Analysis and Nearest Flat in the Least Square Sense. Journal of Optimization Theory and Applications, 2014, DOI: 10.1007/s10957-014-0647-y.
  • Chun-Na Li, Yun-Feng Huang, He-Ji Wu, Yuan-Hai Shao*, Zhi-Min Yang. Multiple recursive projection twin support vector machine for multi-class classification. International Journal of Machine Learning and Cybernetics, 2014, DOI: 10.1007/s13042-014-0289-2.
  • Zhen Wang , Yuan-Hai Shao*, Lan Bai, Nai-Yang Deng. Twin Support Vector Machine for Clustering. IEEE Transactions on Neural Networks and Learning Systems, 2014, DOI: 10.1109/TNNLS.2014.2379930. [Code].
  • Chun-Na Li, Yuan-Hai Shao*, Nai-Yang Deng. Robust L1-norm nonparallel proximal support vector machine. Optimization, 2014, DOI: 10.1080/02331934.2014.994627. [Code].
  • Yuan-Hai Shao*, Chun-Na Li, Zhen Wang , Ming-Zeng Liu, Nai-Yang Deng. Proximal Classifier via Absolute Value Inequalities. In: Proceedings of the 14th IEEE International Conference on Data Mining Workshops (ICDM'14), Shenzhen, China, 2014.
  • Yuan-Hai Shao, Wei-Jie Chen,Zhen Wang, Hai-Bin Zhang, Nai-Yang Deng*. A proximal classifier with positive and negative local regions. Neurocomputing, 2014, 145:131-139.
  • Yuan-Hai Shao, Zhen Wang, Zhi-Min Yang*, Nai-Yang Deng*. Weighted linear loss support vector machine for large scale problems. Procedia Computer Science(IAITQM), 2014,31C: 639-647.
  • Wei-Jie Chen*, Yuan-Hai Shao*, Nai-Yang Deng, Zhi-Lin Feng. Laplacian least squares twin support vector machine for semi-supervised classification. Neurocomputing, 2014,145:465-476.
  • Yuan-Hai Shao, Wei-Jie Chen, Jing-jing Zhang, Zhen Wang, Nai-Yang Deng*. An efficient weighted Lagrangian twin support vector machine for imbalanced data classification. Pattern Recognition, 2014, 47(9): 3158-3167.[Code].
  • Lan Bai, Zhen Wang, Yuan-Hai Shao*, Nai-Yang Deng. A novel feature selection method for twin support vector machine. Knowledge-Based Systems, 2014, 59 1-8.[Code].
  • Yuan-Hai Shao, Wei-Jie Chen,Nai-Yang Deng*. Nonparallel hyperplane support vector machine for binary classification problems. Information Sciences, 2014, 263(1) 2014, 22每35.[Code].
  • Wei-Jie Chen*,Yuan-Hai Shao, Deng-Ke Xu, Yong-Feng Fu. Manifold proximal support vector machine for semi-supervised classification. Applied Intelligence, 2014,40(4):623-638.
  • Wei-Jie Chen*,Yuan-Hai Shao, Ning Hong. Laplacian smooth twin support vector machine for semi-supervised classification[J]. International Journal of Machine Learning and Cybernetics. 2014,5(3):459每468
  • Zhen Wang*, Yuan-Hai Shao, Tie-Ru Wu. Proximal parametric-margin support vector classifier and its applications. Neural Computing and Applications, 2014, 23 (7-8), 2159-2166
  • Yuan-Hai Shao, Nai-Yang Deng*, Wei-Jie Chen. A proximal classifier with consistency. Knowledge-Based Systems, 2013, 49:171-178 [Code].
  • Zhi-Min Yang, Yuan-Hai Shao*, Jing Liang. Unascertained Support Vector Machines. Acta Automatica Sinica (In Chinese), 2013,39 (6): 895-901.
  • Yuan-Hai Shao*, Lan Bai, Zhen Wang, Xiang-Yu Hua, Nai-Yang Deng. Proximal Plane Clustering via Eigenvalues. Procedia Computer Science(IAITQM), 2013,17: 41每47.
  • Zhi-Min Yang, Jun-Yun He*, Yuan-Hai Shao. Feature Selection Based on Linear Twin Support Vector Machines. Procedia Computer Science (IAITQM), 2013,17: 1039-1046.
  • Yuan-Hai Shao*, Wei-Jie Chen, Wen-Biao Huang, Zhi-Min Yang, Nai-Yang Deng*. The Best Separating Decision Tree Twin Support Vector Machine for Multi-Class Classification. Procedia Computer Science (IAITQM), 2013,17: 1032-1038.
  • Wei-Jie Chen*, Yuan-Hai Shao*, Ya-Fen Ye. Improving Lap-TSVM with successive overrelaxation and differential evolution. Procedia Computer Science(IAITQM), 2013, 17: 33每40.
  • Ya-Fen Ye, Hui Cao*, Lan Bai, Zhen Wang, Yuan-Hai Shao. Exploring Determinants of Inflation in China Based on L1-Epsilon-Twin Support Vector Regression. Procedia Computer Science (IAITQM), 2013,17:514每522.
  • Yuan-Hai Shao, Zhen Wang, Wei-Jie Chen, Nai-Yang Deng*. Least squares twin parametric-margin support vector machines for classification. Applied Intelligence, 2013,39(3):451-464.
  • Zhen Wang*, Yuan-Hai Shao, Tie-Ru Wu. A GA-based Model Selection for Smooth Twin Parametric-Margin Support Vector Machine. Pattern Recognition,2013, 46: 2267每2277. [Code].
  • Yuan-Hai Shao*, Nai-Yang Deng, Wei-Jie Chen, Zhen Wang. Improved generalized eigenvalue proximal support vector machine. IEEE Signal Processing Letters, 2013, 20(3):213- 216.
  • Yuan-Hai Shao, Zhen Wang , Wei-Jie Chen, Nai-Yang Deng*. A regularization for the projection twin support vector machine. Knowledge-Based Systems, 2013,37:203每210.
  • Yuan-Hai Shao, Chun-Hua Zhang*, Zhi-Min Yang, Ling Jing, Nai-Yang Deng*. An \varepsilon-twin support vector machine for regression. Neural Computing and Applications,2013, 23:175每185 [Code].
  • Yuan-Hai Shao, Nai-Yang Deng*. A novel margin based twin support vector machine with unity norm hyperplanes. Neural Computing and Applications, 2013, 22(7-8):1627-1635.
  • Zhi-Xia Yang*, Yuan-Hai Shao, Xiang-Sun Zhang. Multiple Birth Support Vector Machine for Multi-class Classification. Neural Computing and Applications, 2013, 22 (Suppl 1):S153每S161.
  • Chun-Hua Zhang, Yuan-Hai Shao, Jun-Yan Tan*, Nai-Yang Deng. Mixed-norm Linear Support Vector Machine. Neural Computing and Applications, 2013, 24 (3-4), 755-764
  • Yuan-Hai Shao*, Nai-Yang Deng, Zhi-Min Yang, Wei-Jie Chen, Zhen Wang. Probabilistic outputs for twin support vector machines. Knowledge-Based Systems, 2012, 33: 145每151. [Code].
  • Yuan-Hai Shao, Nai-Yang Deng*. A coordinate descent margin based-twin support vector machine for classification. Neural Networks, 2012, 25: 114-121.
  • Yuan-Hai Shao, Nai-Yang Deng*, Zhi-Min Yang. Least squares recursive projection twin support vector machine for classification. Pattern Recognition, 2012, 45(6): 2299-2307. [Code].
  • Yuan-Hai Shao, Chun-Hua Zhang, Xiao-Bo Wang, Nai-Yang Deng*. Improvements on Twin Support Vector Machines. IEEE Transactions on Neural Networks, vol.22 no.6 pp. 962-968, 2011. [Code] [Data].
  • Yu-Xin Li, Yuan-Hai Shao, Nai-Yang Deng*. Improved Prediction of Palmitoylation SitesUsing PWMs and SVM. Protein \& Peptide Letters,2011, 18(2): 186-193(8).[Code]
  • Yu-Xin Li, Yuan-Hai Shao, Ling Jing, Nai-Yang Deng*. An Efficient Support Vector Machine Approach for Identifying Protein S-Nitrosylation Sites. Protein \& Peptide Letters, 2011, 18(6): 573-587(15).

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