Brief CV

Wang Xizhao, Ph.D. (1998), Professor (1998), IEEE Fellow (2012), CAAI Fellow (2017), Editor-in-Chief of Springer Journal Machine Learning and Cybernetics (2010), Deputy chair of CAAI machine learning committee (2012), and knowledge engineering committee (2013), overseas high-level (peacock B class) talent of Shenzhen city (2015), prizewinner of First-Class Award of Natural Science Advances of Hebei Province (2007), and Model Teacher of China (2009).

Prof. Wang received his doctor degree in computer science from Harbin Institute of Technology in September 1998. From 1998 to 2001 Prof. Wang worked at Department of Computing in Hong Kong Polytechnic University as a research fellow. From October 2000 to March 2014 Prof. Wang served in Hebei University as the Dean of school of Mathematics and Computer Sciences. From October 2007 to March 2014 Prof. Wang was the founding Director of Key Lab. on Machine Learning and Computational Intelligence in Hebei Province, China. From September to November in 2013, Prof. Wang was a visiting professor of Canada Simon Fraser University. From December 2013 to January 2014, Prof. Wang was a visiting professor of University of Alberta in Canada. From July to September in 2014, Prof. Wang was a visiting professor of Australia New South Wales University at Canberra. Since March 2014 to now Prof. Wang has moved to college of computer science and software engineering in Shenzhen University as a professor and a director of Big Data Institute.

Prof. Wang's main research interest is machine learning and uncertainty information processing including inductive learning with fuzzy representation, approximate reasoning and expert systems, neural networks and their sensitivity analysis, statistical learning theory, fuzzy measures and fuzzy integrals, random weight network, and the recent topic: machine learning theories and methodologies in Big-Data environment. The main research feature is, through discovering and representing the uncertainty hidden in big data, to dig the distribution of big data and then use distributed parallel technology to design and implement classification and clustering algorithms which are suitable for different types of big data. It focuses on the corresponding key issues of theory and technology of big data analytics.

Academic contributions: (1) Putting forward the concept of "fuzzy learning from examples" for the first time in 1996 during his PhD thesis, and extending machine learning approaches into the uncertainty framework. His research in this aspect lasted almost 20 years and acquired a series of achievements with significant impact, for example, the project “fuzzy-valued attribute feature subset selection” won the first prize of Hebei province natural science in 2007. (2) Establishing a refinement methodology and technique for similarity based clustering, called departure-0,5, and extending it to a new branch of semi-supervised learning based on departure-0.5, and further applying successfully to the big data learning. Mainly due to this contribution Prof. Wang was elected as an IEEE Fellow in 2012. (3). Proposing the viewpoint that uncertainty modeling and its effective handling play a crucial/indispensible role in improving the generalization ability for a big data learning system. The view point is highly recognized by the experts in related domains, and is funded by a NSFC key project (Uncertainty modeling in learning from big data, 2018-2022).

Research achievements: Prof. Wang has published 3 monographs and 2 textbooks. He has also published 200+ research papers in famous magazine and conferences in the field of machine learning and uncertainty, among which 150+ publications have been included in SCI or EI databases. The journals include IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Cybernetics, Machine Learning, Information Sciences and Fuzzy Sets and Systems. By Google scholar in November 2017, the total number of citations is 6360, the maximum number of citations for a single paper is 600, and the SCI-H index is 42. Prof. Wang has completed 30+ research projects including ones funded by National Natural Sciences Fund of China, by Ministry of Education, by National Development and Reform Commission, by Hebei Province Natural Science, and by RGC in Hong Kong.

Awards and honors: Prof. Wang has received the First-Class Award of Natural Science Advances of Hebei Province and the Second-Class Award of Natural Science of Education Ministry in 2007. He was selected as one member of the first hundred of excellent innovative talents of Hebei province in 2007. He gained the honor of Model Teacher of China in 2009. Prof. Wang was evaluated as an IEEE Fellow in 2012 and a CAAI Fellow in 2017. He was chosen as the local leading talent of Shenzhen in 2013 and one of the Chinese scholars whose academic papers have been highly cited based on Elsevier statistics in 2014/15/16. Prof. Wang was identified as the overseas high-level (peacock B class) talent of Shenzhen in 2015.

Education

1998.09 PhD in Computer Science from Harbin Institute of Technology
1995.09-1996.07 PhD candidate at Dept. of Computer Science in Harbin Institute of Technology
1990.02 Master Degree in Mathematics from Hebei University
1985.09-1987.07 Postgraduate at Department of Mathematics in Shanghai Jiaotong University
1983.07 Bachelor Degree in Mathematics from Hebei University
1979.09-1983.06 Undergraduate at Department of Mathematics in Hebei University

Working

2014.03-now Prof./Doctoral tutor, College of Computer Science & Software Engineering, Shenzhen Univ
2000.10-2014.03 Dean/Prof., School of Mathematics and Computer Sciences, Hebei Univ
1998.09-2001.09 Research Fellow, Dept. of Computing, Hong Kong Polytechnic Univ
1998.11-2013.05 Full Professor, School of Mathematics and Computer Sciences, Hebei Univ
1993.07-1998.10 Associate Professor, Dept. of Mathematics, Hebei University
1988.02-1993.06 Lecturer, Dept. of Mathematics, Hebei University
1983.07-1988.01 Teaching Assistant, Dept. of Mathematics, Hebei University

Teaching

Since September 1983, Prof. Wang has delivered for undergraduates, postgraduates, and PhD candidates 50+ courses including the following: Mathematical Analysis, Linear Algebra, Analytic Geometry, Numerical Algebra, Numerical approximation, Discrete Equations, Numerical Solution of Nonlinear Equations, Numerical Solution of Partially Differential Equations, Probability and Statistics, Linear Model, Multi-variant Statistics, Mathematical Modeling, BASIC, FORTRAN, PASCAL, FOXPRO, C/C++, Data Structure, Algorithm Analysis, Artificial Intelligence, Machine Learning, Neural Networks, Genetic Algorithms, Fuzzy Set Theory, Fuzzy Logic, Fuzzy Measures and Integrals, Fuzzy Statistics, Neural Networks and Fuzzy Control, Fuzzy Expert Systems, Neuro-Fuzzy systems, Data Mining, Statistical Learning Theory, Rough Set Theory and Its Applications.
The course "Numerical Approximation" developed and delivered by Prof. Wang and his team was evaluated a Province-Level Model Course in Hebei Province in 2004.

Courses in the first semester in 2017-2018
1. Machine Learning
2. Statistical Learning Theory

Courses in the first semester in 2016-2017
1. Machine Learning
2. Statistical Learning Theory

Courses in the second semester in 2016-2017
1. Matrix Theory

Courses in the first semester in 2015-2016
1. Data warehouse and data mining

Courses in the first semester in 2014-2015
1. Data Mining
2. Statistical Learning Theory


Since 1996, Prof. Wang has trained more than 160 graduate students. Some graduate students are as follows.


Ph.D Candidates Master Degree Candidates(Computer Science) Master Degree Candidates(Mathmatics)
2017, Computer Science, Muhammed Jamshed Alam Patwary
2017, Computer Science, Salim Rezvani
2017: Lei Hu, Shu-Yue Chen, Da-Sen Yan, Xin-Lei Zhou
2015, Management Science and Engineering, Yan-Xia Zhao
2015, Computer Science, Hong Zhu
2015: Peng Yao, Hong-Yu Zhu
2013, Management Science and Engineering, Shi-Xin Zhao
2012, Management Science and Engineering, Sheng Xing

Graduated Ph.D Students
2012-2017, Management Science and Engineering, Sheng Xing
2015-2017 Communication Engineering discipline point: Aamir Raza Ashfaq
2011-2015 Management Science and Engineering: Ai-Min Fu
2010-2014, Management Science and Engineering: Abdallah Bashir Musa Hme
2009-2014, Optical Engineering: Yu-Lin He
2006-2010, Optical Engineering: Jun-Hai Zhai
2003-2007, Optical Engineering: Shu-Xia Lu

Graduated Master students
Computer Science Mathematics
2014 Zhi Wang, Xing-Ming Zhao Fan Zhang, Xin-Yi Cui
2013 Tian-Lun Zhang(Software Engineering) Pei-Zhou Zhang
2012 Hong Zhu, Shan-Shan Wang, Dong-Hui Wang
2011 Jian Zhang, Pan Pan Xin Wang, Jian-Kai Chen
2010 Qing Miao, Qing-Yan Shao, Ta Li Meng Zhang, Gui-Qiang Zhang, Hua Li
2009 Ting-Ting Wang, Tie-Song Li, Jian-Guo Wu Fang-Fang Cui, Yan Geng, Li-Jie Bai
2008 Pan Su, Yue Gao, Wen-Liang Li, Bo-Yi Zhao, Zhen-Yu Wang, Li-Li Sun,Hua-Chao Wang, Chen-Yan Bai Jin Zhao, Xiu-Li Zhang, Na-Xin Sun, Gui-En Cao, Jie Meng
2007 Yue Zhang, Sheng-Min Zhang, Chan-Chan Zhang, Xiang-Ran Du, Shuo Wang, Ling-Cai Dong, Jie Chen, Shan Su, Hui-Qin Zhao, Qing-Wu Meng Wei-Yun Yan, Hui-Min Ma, Yan-Zheng Mu, Ying Zhang
2006 Ning Zhang, Bo Wu, Xiang-Hao Pei, Yu-Lin He, Han-Xue Hao, Qian Li,Feng Guo, Hai-Feng Li, Sheng Xing, Qing-Sheng Zhang Huan-Yu Zhao, Cui-Lian Zhou, Li-Hua Wang, Qun-Duo Wu
2005 Li-Mei Feng, Ning Zhang, Wei-Xi Lin, Hai-Bo Wang, Wei-Li Zhang, Dong-Lei Zhao,Jia-Lin Chen, Lian-Lei Huo Xiao-Yan Liu, Jin-Yan Sun, Bin Wu, Yan-Dong Ma,Chun-Yu Feng, Jie Li
2004 Chen-Xiao Yang, Ming-Zhu Lu, Jian-Bing Huo, Jian-Hui Yan, Xiang-Hui Gao, Ning Li, Lei Han, Jie Zhu, Lei Wang Li Zhao, Ai-Xia Chen, Li-Rong Liu, Shao-Hong Li,Guo-Fang Zhang, Feng Yang
2003 Kai Xie, Yan-Jun Dong, Xin Tian, Lei-Fan Yan, Ying Xu, Ya-Qian Zhao,Su-Fang An, Miao Wang, Yan Ha, Lin-Yan Xue, Ya-Hui Xi, Bo-Jun Xie Su-Fang Zhang, Lian-Bao Zhao, Hui Zhang, Xu-Guang Wang, Yu-Fei Zhang, Jun Shen, Chun-Guo Li
2002 Chun-Ru Dong, Guang-Ming Hu, Ji-Guang Rong, Hao Chen, Jing-Hong Wang, Zhi-Jing Feng, Xiao-Ying Lu Hui-Min Feng, Xiao-Jun Wang, Tie-Gang Fan, Jun-Fei Chen, Jing Wu, Yong-Li Su
2001 Zi-Ying You, Han-Ying Zheng, Yong Li, Jing-Bo Xie Su-Yun Zhao, Shi-Xin Zhao, Hua Li, Qun-Feng Zhang
2000 Juan Sun, Yan Zhan, Li-Juan Wang, Hong-Wei Yang, Ming-Hua Zhao, Jin-Feng Wang Qiang He, Hong-Jie Xing
1999 Lan-Zhen Yang, Rui-Xing Wang, Ben Niu
1998 Yan Li, Feng Zhang, Li-Min Wang
1996 Qiang Hua, Dong-Mei Huang

Awards

Membership

Membership

IEEE Fellow 
CAAI Fellow
IEEE-SMC Board of Governor Member (2005, 2007-2009, 2012-2014) 
Chair, IEEE-SMC Technical Committee on Computational Intelligence 
Chair, IEEE SMC Baoding Chapter 
Editor-in-Chief, Springer Journal Machine Learning and Cybernetics 
Associate Editor, IEEE Transactions on SMC Part (B) 
Associate Editor, Information Sciences 
Associate Editor, Pattern Recognition and Artificial Intelligence 
Member, The 6th China Association of Industrial and Applied Mathematics (CAIAM) 
Member, The 5th, 6th China Association of Artificial Intelligence (CAAI) 
Co-chair, The 6th CAAI Technical Committee on Knowledge Engineering 
Executive Member, The 5th, 6th CAAI Technical Committee on Machine Learning 
Vice chairman of the seventh Machine Learning Professional Committee of China Society of Artificial Intelligence
Executive Member, The 2nd, 3rd CAAI Technical Committee on Rough Set 
Chair, The 1st, 2nd Machine Learning Society in Hebei Province 
Vice chair, The 3rd society of Industrial and Applied Mathematics in Hebei Province 
Vice chair, Artificial Intelligence in Hebei Province 
Head, Organizing Committee of Mathematical Modeling Content in Hebei Province 
Editorial Member, Chinese Journal of Fuzzy Systems and Mathematics 



Community Services

Area Chair, ELM2016 (Maria Bay Sands, Singapore) 
Penal Discussion Organizer: Deep learning with big data, ICMLC2016 (Jeju Island, Korea) 
Conference Chair: ICMLC (International Conference on Machine Learning and Cybernetics) 2016
Organizer: Big data machine learning BBS, Shenzhen University, December 20-23, 2015
Penal Discussion Organizer: Learning from Big Data, in ICMLC2015 
Conference Chair: ICMLC (International Conference on Machine Learning and Cybernetics) 2015
Penal Discussion Organizer: Big Data with Uncertainty, in ICMLC2014 
Conference Chair: ICMLC (International Conference on Machine Learning and Cybernetics) 2002-2014 
Conference Chair: ICWAPR (International Conference on Wavelet Analysis and Pattern Recognition) 2009-2013 
Reviewer Chair: CYBCONF2013 (IEEE International Conference on Cybernetics) 
Organization Chair: ELM2011 (The International Symposium on Extreme Learning Machines) 
PC Chair: The fourteenth China Conference on Machine Leaning, 2013 
PC Chair: ELM2012-2013 (The International Conference on Extreme Learning Machines) 
PC Chair: IEEESMC (IEEE International Conference on Systems, Man, and Cybernetics) 2008-2011 
PC Chair: IEA-AIE 2014 (The 27th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (http://bit.kuas.edu.tw/~ieaaie14)) June 3-6, 2014 Kaohsiung, Taiwan 
Easy-Chair Account (May 2013): 1. AI 11: PC member// 2. AMLTA2012: PC member// 3. CCML2013: chair// 4. CRSSC-CWI-CGrC 2013: PC member// 5. CRSSC-CWI-CGrC'2011: PC member// 6. DS 2013: PC member// 7. MLA 2013 Workshop: chair// 8. MLFD 2012: chair// 9. NCIIP2013: PC member// 10. RSFDGrC-2011: PC member// 11. SMC2010: track chair

Visiting

  • [101]
    November 24-26, 2017, Shaoguan College, Shaoguan
  • [100]
    International Conference of IDEAL, October 29-31, 2017, Guilin, China
  • [99]
    October 27-29, 2017, Hubei National Normal University, Enshi, China
  • [98]
    International Conference of ELM, October 6-7, 2017, Yantai, China
  • [97]
    Smart city seminar, September 15-18, 2017, Beijing Architecture University, Beijing
  • [96]
    Standing committee of rough set, August 18-20, 2017, Dujiangyan, China
  • [95]
    International Conference of SKG, August 14-15, 2017, Beijing
  • [94]
    CCML, July 26-28, 2017, Tianjin
  • [93]
    Concept lattice seminar, July 18-21, 2017, Xi’an
  • [92]
    International Journal of Machine Learning and Cybernetics, July 9-12, 2017, Ningbo
  • [91]
    Xinjiang Shihezi University,June 28-July 4, 2017, Shihezi
  • [90]
    Zhangzhou Normal College(Minnan University), June 7-9, 2017, Zhangzhou
  • [89]
    Prep-ICMLC 2018, June 4-6, 2017, Chengdu
  • [88]
    National Conference on Intelligent Information Processing,May 12-14, 2017, Xinxiang
  • [87]
    Review Conference for CCML, May 3-6, 2017, Jinnan
  • [86]
    Standing committee of CCML, April 8-9, 2017, Suzhou University
  • [85]
    Review Conference for NCIIP, March 24-26, 2017, Xinxiang
  • [84]
    Prep conference for ICMLC, January 16-18, 2017, Ningbo
  • [83]
    China Mining University, January 5-6, 2017, Xuzhou
  • [82]
    National University of Singapore, January 1-4, 2017, Singapore
  • [81]
    Zhongshan University, December 16-17, 2016, Zhongshan
  • [80]
    Fujian normal university, December 13-14, 2016, Fuzhou
  • [79]
    Conference on Fuzzy Systems and Data Mining, December 11-12, 2016, Macau
  • [78]
    Macau University of Science and Technology, December 8-10, 2016, Macau
  • [77]
    Hong Kong education college, November 8, 2016, Hong Kong
  • [76]
    Caritas Institute of Higher Education, November 7, 2016, Hong Kong
  • [75]
    Particle calculation and big data BBS, Oct. 28-30, 2016, Zhoushan
  • [74]
    Nanjing University of Aeronautics and Astronautics, October 23-24, 2016, Nanjing
  • [73]
    Concept grid and big data seminar, Kunming University of Technology, October 21-23, 2016, Kunming
  • [72]
    IEEE SMC, October 8-15, 2016 Budapest, Hungary
  • [71]
    Formal Concept Analysis and Granular Computing Symposium, July 27-30, 2016, Chongqing University of Technology, Chongqing, China
  • [70]
    ICMLC2016, July 10-13, 2016, Maison Glad Hotel, Jeju Island, Korea
  • [69]
    IEEE SMC Celebration Lecture Series, July 7-9, 2016, Southwest Jiaotong University, Chengdu
  • [68]
    Big data and intelligent control forum, Jun 24-26, 2016, Beijing Normal University Zhuhai Campus, Zhuhai
  • [67]
    Big Data and Uncertainty Analysis Forum, May 18, 2016, Ningbo Institute of science and technology, Zhejiang University, Ningbo
  • [66]
    Big Data and Uncertainty Modeling Discussion, April 21, 2016, Railway University, Shijiazhuang
  • [65]
    Big Data and Uncertainty Modeling Discussion, April 14, 2016, Beijing Architectural Engineering University, Beijing
  • [64]
    Big data and pattern analysis forum, April 10-13, 2016, Jiangsu University of Science and Technology, Zhejiang
  • [63]
    Big Data Machine Learning Forum, December 20-23, 2015, Big data center of Shenzhen University, Shenzhen
  • [62]
    IEEE SMC, October 9-12 2015, Hong Kong
  • [61]
    CCML2015 (China Conference on Machine Learning), August 16-18 2015, Chengdu
  • [60]
    China Mathematical Modeling 17th Annual Meeting, August 14-17 2015, Baoding
  • [59]
    NCIIP2015(National Conference on Intelligent Information Processing), August 5-7 2015, Qingdao
  • [58]
    ICMLC2015, Jun 12-15, 2015, Guangzhou
  • [57]
    Being Visiting Scholar at University of New South Wales at Canberra, Australia, July 23 - September 22, 2014, Canberra, Australia
  • [56]
    The 13th International Conference on Machine Learning and Cybernetics, July 13-15, 2014, Lanzhou, China
  • [55]
    Visiting The Department of Software, Northeast University, May 11-13, 2014, Shenyang, China
  • [54]
    Visiting Illinois University at Champion-Urbana, December 23, 2013 - January 3, 2014, Champion-Urbana, USA
  • [53]
    Visiting Aberystwyth university, UK, October 16-17, 2013, Aberystwyth, UK
  • [52]
    IEEESMC2013, October 12-15, 2013, Manchester, UK
  • [51]
    Being Visiting Scholar at University of Alberta, Canada, December 25, 2013 - January 25, 2014, Alberta, Canada
  • [50]
    Being Visiting Scholar at Simon Fraser University, Canada, September 25 - December 25, 2013, Vancouver, Canada
  • [49]
    A Symposium on Random Weight Networks, August 6-8, Yinchuan, China
  • [48]
    A Workshop on Machine Learning & its Application, August 2-5, Hohhot, China
  • [47]
    A Workshop on Big Data in Tianjin, August 1, 2013, Tianjin, China
  • [46]
    The 9th China Annual Conference on Uncertainty, August 28-29, 2013, Handan, China
  • [45]
    NCIIP2013, July 26-28, 2013, Nanning, China
  • [44]
    CCML2013, August 16-18, 2013, Kunming, China
  • [43]
    The 12th International Conference on Machine Learning and Cybernetics, July 13-15, Tianjin, China
  • [42]
    IEEE SMC Lecture Celebration Series, July 10-12, 2013, Baoding, China
  • [41]
    The third International Symposium on Extreme Learning Machines, December 11-13, 2012, Singapore
  • [40]
    IEEE International Conference on Systems, Man & Cybernetics, October 9-12, 2012, Korea
  • [39]
    International Conference on Machine Learning and Cybernetics, July 15-17, 2012, Xi'an
  • [38]
    The second International Symposium on Extreme Learning Machines, December 6-8, 2011, Hangzhou
  • [37]
    The 13th China Conference on Machine Learning and Cybernetics, August 6-8, 2011, Wuyishan, China
  • [36]
    International Conference on Machine Learning and Cybernetics, July 10-13, 2011, Guilin
  • [35]
    The first International Symposium on Extreme Learning Machines, December 7, 2010, Australia
  • [34]
    The 3rd National Conference on Intelligent Information Processing, August 12-14, 2010, Taiyuan, China
  • [33]
    The 12th China Conference on Machine Learning (CCM2010), August 6-8, 2010, Jinan, China
  • [32]
    IEEE International Conference on Systems, Man & Cybernetics, October 10-13, 2010, Turkey
  • [31]
    International Conference on Machine Learning and Cybernetics, July 7-14, 2010, Qingdao
  • [30]
    China Conference on Data Mining, May 6-9, 2010, Guangzhou
  • [29]
    International Conference on Rough Sets, Fuzzy sets, Data mining and Granular Computer, December 18-23, 2009, Indian Institute of Technology, New Delhi
  • [28]
    IEEE International Conference on Systems, Man & Cybernetics, October 11-14, 2009, USA
  • [27]
    International Conference on Machine Learning and Cybernetics, July 12-15, 2009, Baoding
  • [26]
    The fourteenth China Congress on Fuzzy Systems and Mathematics, October 31-November 3, 2008, Wuyishan
  • [25]
    IEEE International Conference on Systems, Man & Cybernetics, October 12-15, 2008, Singapore
  • [24]
    International Conference on Machine Learning and Cybernetics, July 12-15, 2008, Kunming
  • [23]
    IEEE International Conference on Systems, Man & Cybernetics, October 7-10, 2007, Canada
  • [22]
    International Conference on Machine Learning and Cybernetics, August 20-23, 2007, Hong Kong
  • [21]
    The tenth China Conference on Machine Leaning, October 13-15, 2006, Haikou
  • [20]
    International Conference on Machine Learning and Cybernetics, 13-16 August 2006
  • [19]
    Asia-Pacific Workshop on Visual Information Processing, December 11-13, 2005, Hong Kong
  • [18]
    The 11th National Annual Conference of Chinese Association for Artificial Intelligence, October 31-November 2, 2005, Wuhan
  • [17]
    IEEE International Conference on Systems, Man & Cybernetics, October 10-12, 2005, USA
  • [16]
    International Conference on Machine Learning and Cybernetics, August 19-21, 2005, Guangzhou
  • [15]
    IFSA World Congress, July 28-31, 2005, Beijing
  • [14]
    IEEE International Conference on Systems, Man & Cybernetics, October 12-15, 2004, Netherlands
  • [13]
    International Conference on Machine Learning and Cybernetics, August 26-29, 2004, Shanghai
  • [12]
    The 10th National Annual Conference of Chinese Association for Artificial Intelligence, November, 2003, Guangzhou
  • [11]
    International Conference on Machine Learning and Cybernetics, November 2-5, 2003, Xi'an
  • [10]
    The 8th China Machine Learning Conference, December, 2002, Guangzhou
  • [9]
    International Conference on Machine Learning and Cybernetics, November 4-5, 2002, Beijing
  • [8]
    Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25-28, 2001, Canada
  • [7]
    IEEE International Conference on Systems, Man & Cybernetics, October 8-11, 2000, USA
  • [6]
    IEEE International Conference on Systems, Man & Cybernetics, October 12-15, 1999, Japan
  • [5]
    The 9th Annual Conference of Chinese Fuzzy Systems and Mathematics, August, 1998, Baoding
  • [4]
    The 7th National Annual Conference of Chinese Fuzzy Systems and Mathematics Committee, August, 1994, Taiyuan
  • [3]
    The 6th Annual Conference of Chinese Fuzzy Systems and Mathematics Committee, August, 1992, Huangshan
  • [2]
    Sino-Japan Joint Meeting on Advanced Fuzzy Sets and Systems, 1990, Beijing
  • [1]
    The fifth Annual Conference of Chinese Fuzzy Systems and Mathematics Committee, August, 1990, Chengdu

Keynotes

  • [63]
    November 24-26, 2017, Shaoguan College, Title: Big data learning with uncertainty
  • [62]
    International Conference of IDEAL, October 29-31, 2017, Guilin, Keynote: Big data learning with uncertainty
  • [61]
    October 27-29, 2017, Hubei National Normal University, Enshi, Title: Big data learning with uncertainty
  • [60]
    International Conference of ELM, October 6-7, 2017, Yantai, Keynote: Big data learning with uncertaint
  • [59]
    International Conference of SKG, August 14-15, 2017, Beijing, Keynote: Learning from big data with uncertainty
  • [58]
    Concept lattice seminar, July 18-21, 2017, Xi’an, Title 1: Non-iterative depth learning; Title 2: Learning from big data with uncertainty
  • [57]
    Zhangzhou Normal College(Minnan University), June 7-9, 2017, Zhangzhou, Title 1: Stock trend forecasting based on deep learning; Title 2: Different writing paper vs proposal
  • [56]
    China Mining University, January 5-6, 2017, Xuzhou, Title 1: Some thinking about deep learning; Title 2: Different writing paper vs proposal
  • [55]
    Zhongshan University, December 16-17, 2016, Zhongshan, Title: Uncertainty in learning from big data
  • [54]
    Fujian normal university, December 13-14, 2016, Fuzhou, Title: Uncertainty in learning from big data
  • [53]
    Conference on Fuzzy Systems and Data Mining, December 11-12, 2016, Macau, Keynote: Uncertainty in learning from big data
  • [52]
    Hong Kong education college, November 8, 2016, Hong Kong, Title: Uncertainty in learning from big data
  • [51]
    Caritas Institute of Higher Education, November 7, 2016, Hong Kong, Title: Uncertainty in learning from big data
  • [50]
    Particle calculation and big data BBS, Oct. 28-30, 2016, Zhoushan, Title: Uncertainty in learning from big data
  • [49]
    Concept grid and big data seminar, Kunming University of Technology, October 21-23, 2016, Kunming, Title: Uncertainty in learning from big data
  • [48]
    IEEE SMC, October 8-15, 2016 Budapest, Hungary, Title: Big data sampling
  • [47]
    July 27-30, 2016, Formal Concept Analysis and Granular Computing Symposium, Chongqing University of Technology, Chongqing, Special Report: Some thinking about deep learning
  • [46]
    July 27-30, 2016, ICMLC2016, Maison Glad Hotel, Jeju Island, Korea, Special Report: Learning from uncertainty for Big Data
  • [45]
    July 7-9, 2016, IEEE SMC Celebration Lecture Series, Southwest JiaoTong University, Report Title: Different Writing: from academic paper to research
  • [44]
    June 24-26, 2016, Big data and intelligent control forum, Beijing Normal University, Zhuhai, Special Report: Learning from uncertainty for Big Data
  • [43]
    April 21, 2016, University of Railway, Shijiazhuang, Special Report: Learning from uncertainty for Big Data
  • [42]
    April 14, 2016, Beijing Architectural Engineering University, Beijing, Special Report: Learning from uncertainty for Big Data
  • [41]
    April 10-13, 2016, Big data and pattern analysis forum, Beijing, Special Report: Learning from uncertainty for Big Data
  • [40]
    October 12, 2015, SMC2015(IEEE International Conference on Systems, Man, and Cybernetics), Hong Kong, http://www.smc2015.org/ , Keynote: Learning from Uncertainty for Big Data
  • [39]
    November 19, 2015, School of mathematics and physics, China Agricultural University, Report Title: Uncertainty learning for big data
  • [38]
    August 14, 2015, National Conference on mathematical modeling 2015, Baoding, Report Title: Big Data Analysis and Modeling
  • [37]
    July 13, 2014, ICMLC2015, Report Title: Big Data and Granular Computing
  • [36]
    September 12, 2014, Seminar in University of New South Wales at Canberra, Australia, Report Title: Learning from Big Symbolic Data
  • [35]
    July 14, 2014, The 13th International Conf. on Machine Learning and Cybernetics, Lanzhou, China, Report Title: Big Data with Uncertainty
  • [34]
    May 12, 2014, Northeast University, Shenyang, China, Report Title: Learning from Big Data
  • [33]
    October 15, 2013, Univ. of Aberystwyth, Uk, Report Title: ELM for Big Data Classification
  • [32]
    August 7, 2013, Workshop on Random Weight Networks, Yinchuan, China, Report Title: Random Weight Neural Network for Big Data Classification
  • [31]
    August 1, 2013, Workshop on big data, Tianjin University, Tianjin, China, Report Title: ELM for Big Data Classification
  • [30]
    July 28, 2013, The 9th China annual conf. on uncertainty systems, Handan, China, Report Title: Big Data Classification under Uncertainty Environment
  • [29]
    July 4, 2013, College of Science, China Agricultural University, Beijing, Report Title: RWN: A New Technology for Machine Learning with Large Data
  • [28]
    June 24, 2013, Shenzhen University, Shenzhen, Report Title: RWN: A New Technology for Machine Learning with Large Data
  • [27]
    April 28, 2013, Lab. of Intelligent Information Processing in Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Report Title: New Advances in Architecture Selection of Random Weight Networks
  • [26]
    December 21, 2012, the City University of Hong Kong, Hong Kong, Report Title: Architecture Selection of RWNs and Their Improved Training Algorithms
  • [25]
    December 12, 2012, 2012 International Symposium on Extreme Learning Machines, Singapore, Report Title: Architecture Selection of RWNs and Their Improved Training Algorithms
  • [24]
    December 9, 2012, Malaysia University of Science and Technology, Malaysia, Report Title: Architecture Selection of RWNs and Their Improved Training Algorithms
  • [23]
    November 28, 2012, Swinburne University, Melbourne, Australia, Report Title: Architecture Selection of RWNs and Their Improved Training Algorithms
  • [22]
    November 27, 2012, The 1st Computer Science Workshop in La Trobe University, Melbourne, Australia, Report Title: Architecture Selection of RWNs and Their Improved Training Algorithms
  • [21]
    October 14-17, 2012, IEEE-SMC Annual Meeting, Board Meeting, Seoul, Korea, A keynote speech has been given
  • [20]
    September 29, 2012, Guangzhou University of Technology, Guangzhou, Report Title: Handling Uncertainty in Supervised Learning
  • [19]
    September 24-28, 2012, City University of Hong Kong, Hong Kong, Report Title: Handling Uncertainty in Supervised Learning
  • [18]
    April 28, 2012, South China University of Technology, Guangzhou, Report Title: Handling Uncertainty in Supervised Learning
  • [17]
    April 25, 2012, Henan Normal University, Xinxiang, Report Title: Uncertainty in Random Weight Network
  • [16]
    March 12th, 2012, Suzhou University, Suzhou, Report Title: Intelligent Information System and Learning in Uncertain Environments
  • [15]
    November 10, 2011, IEEE-SMC Distinguished Lecture Program, City University of Hong Kong, Hong Kong, Report Title: Handling Uncertainty in Supervised Learning
  • [14]
    November 2, 2011, Hebei University, Baoding, Title: Handling Uncertainty in Supervised Learning
  • [13]
    September 7, 2011, IEEE-SMC Distinguished Lecture Program, Hong Kong Polytechnic University, Hong Kong, Report Title: Different Writing: from Academic Papers to Research Proposals
  • [12]
    August 29, 2011, Sun Yat-sen University, Guangzhou, Title: Handling Uncertainty in Supervised Learning
  • [11]
    August 26, 2011, IEEE-SMC Distinguished Lecture Program, Hong Kong Polytechnic University, Hong Kong, Report Title: Handling Uncertainty in Supervised Learning
  • [10]
    June 2010, Xinxiang University, Xinxiang, Report Title: Inverse Problem of Support Vector Machines and Its Applications
  • [9]
    August 2009, the 9th Conference of China Rough Set and Soft Computing, Hebei Normal University, Shijiazhuang, Report Title: A Comparative Study on Rule Generation Between Decision-tree-based and Rough-set-based Approaches
  • [8]
    May 10, 2009, Zhejiang Ocean University, Zhoushan, Report Title: Sample Selection Based on Maximum Uncertainty
  • [7]
    December 8, 2008, IEEE-SMC Distinguished Lecture Program, National Taiwan University of Science and Technology, Taiwan, Report Title: Sample Selection Based on Maximum Uncertainty
  • [6]
    December 5, 2008, 2008 Workshop on Consumer Electronics, Jinwen University of Science and Technology, Taiwan, Report Title: Fuzzy Integral and Its Application to Classification
  • [5]
    October 31, 2008, The 14th China Fuzzy Mathematics and Fuzzy Systems Conference, Fujian, Title: Fuzzy Integral and Its Application to Classification
  • [4]
    September 22, 2008, IEEE-SMC Distinguished Lecture Program, City University of Hong Kong, Hong Kong, Report Title: Fuzzy Integral and Its Application to Classification
  • [3]
    September 18, 2006, 2006 Asian Fuzzy Systems Society International Conference, Baoding, Report Title: Information Fusion based on Fuzzy Integrals and Its Application to Classification
  • [2]
    October 10, 2006, The 13th China Fuzzy Mathematics and Fuzzy Systems Conference, Shaanxi Normal University, Xi'an, Title: Theoretical Foundations of Statistical Learning Theory and Research on the Generalization of SVM
  • [1]
    August 15, 2006, International Conference on Machine Learning and Cybernetics, Dalian, the report topic: SVM Inverse Problem and Its Application to Decision Tree Induction

Projects

Edited SI

  • [14]
    Special Issue on Integrated Computing: Computational Intelligence Paradigms and Internet of Things for Industrial Applications IEEE Internet of Things Journal (Volume: 5, Issue: 3, June 2018) Guest Editors: Joel J. P. C. Rodrigues; Xizhao Wang; Arun Kumar Sangaiah; Michael Sheng
  • [13]
    Journal of Applied Soft Computing, Special issue title: Applying Machine Learning Systems for IoT Services in Industrial Informatics, Guest editors: Xizhao Wang, Arun Kumar Sangaiah, Michael Sheng, Ongoing
  • [12]
    Journal of Soft Computing, Special issue title: Non-iterative approaches to training feed-forward neural networks and their applications, Guest editors: Xizhao Wang and Arun Kumar Sangaiah, Ongoing
  • [11]
    CCIS (Communications in Computer and Information Science) 481, Springer, The 13 International Conference on Machine Learning and Cybernetics, Lanzhou, China, 13-16.Editors: Xi-zhao Wang, WitoldPedrycz, Patrick Chan and Qiang HeX. Z. Wang, W. Pedrycz, P. Chan, Q. He. Machine Learning and Cybernetics, 13th International Conference, Lanzhou, China, July 13-16, 2014. Proceedings. Communications in Computer and Information Science, springer, 2014.
  • [10]
    Journal of Intelligent and Fuzzy Systems (JIFS):
Special Issue on Learning from Big Data with Uncertainty (LBDU); Guest Editor: Xi-Zhao Wang, 2015X. Z. Wang. Learning from big data with uncertainty - editorial. Journal of Intelligent & Fuzzy Systems, 2015, 28(5): 2329-2330.
  • [9]
    “Uncertainty in Learning from Big Data”, Special Issue in Int. Journal of Fuzzy Sets and Systems, Elsevier Inc., Edited by Xi-zhao Wang, et al, 2015 http://www.journals.elsevier.com/fuzzy-sets-and-systems/call-for-papers/call-for-papers-uncertainty-in-learning-from-big-data/.X. Z. Wang, J. Z. X. Huang. Editorial: Uncertainty in learning from big data. Fuzzy Sets and Systems, 2015, 258: 1-4.
  • [8]
    “Uncertainty and Extreme Learning Machine”, Special Issue in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, World Scientific Publishing Co., Edited by Xi-zhao Wang, et al, 2013 (in progress).X. Z. Wang. Special Issue on Extreme Learning Machine with Uncertainty. Guest editors' introduction. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2013, 21(supp02): v-vi.
  • [7]
    “Intelligent Web Information System and Learning in Uncertain Environments”, Special Issue in Int. Journal of World Wide Web, Springer-Verlag, Edited by Xi-zhao Wang, Hui Wang, 2014.X. Z. Wang, H. Wang. Guest editorial: learning from uncertainty and its application to intelligent systems of web information. World Wide Web, 2014, 17: 1027-1028.
  • [6]
    “Extreme learning machine”, Special Issue of Soft computing, Springer-Verlag, Edited by Xi-zhao Wang, Dianhui Wang, Guangbin Huang, 2011.X. Z. Wang, D. H. Wang, G. B. Huang. Editorial of special issue: ELM2011. 2012, 16(9): 1461-1463.
  • [5]
    “Soft Computing on Machine Learning and Cybernetics”, Special Issue of Soft computing, Springer-Verlag, Edited by Witold Pedrycz, Daniel Yeung, Xi-zhao Wang, 2011.W. Pedrycz, D. Yeung, X. Z. Wang. Recent advances on machine learning and Cybernetics. Soft Computing, 2011, 15(6): 1039-1039.
  • [4]
    “Recent advance in granular computing”, Special Issue of Information sciences, Elsevier Inc., Edited by Daniel, Yeung, Xi-zhao Wang, De-Gang Chen, 2008.D. Yeung, X. Z. Wang, D. G. Chen. Recent advances in granular computing - Preface. Information sciences, 2008, 178: 3161-3162.
  • [3]
    “Learning with fuzzy representation and its application to pattern recognition”, Special Issue of the International Journal of Pattern Recognition and Artificial Intelligence, World Scientific Publishing Co., Edited by Xi-zhao Wang, Y. Y. Tang, Daniel Yeung, 2008. X. Z. Wang, Y. Y. Tang, D. Yeung. Editorial of special issue: Learning under Uncertain Environment and Its Application to Pattern Recognition. International Journal of Pattern Recognition and Artificial Intelligence, 2008, 22(01): 1-2.
  • [2]
    “Machine learning techniques: problems and applications”, Special Issue of Soft computing, Springer-Verlag, Edited by Zhi-Qiang Liu, Daniel So Yeung, Xi-zhao Wang, Eric Tsang, 2006. Z. Q. Liu, D. Yeung, X. Z. Wang, E. Tsang, J. Lee. Preface for the special issue: soft computing in machine learning and cybernetics. Soft Computing, 2006, 10(1): 1-1.
  • [1]
    "Fuzzy Sets Theory and Applications" Chinese Ninth Meeting of Fuzzy Mathematics and Fuzzy Systems Committee Selected Papers Ying-Ming Liu, Cong-Xin Wu, Xi-Zhao Wang 1998

Monographs

  • [6]
    Xizhao Wang and Junhai Zhai, Learning with Uncertainty, CRC Press Talor & Francis Group, 2016outline
  • [5]
    Xizhao Wang, Junhai Zhai, Induction of decision trees based on uncertainty, China Science Press, 2012(Chinese)outline
  • [4]
    Xizhao Wang, Fuzzy measures and fuzzy integrals and their applications in Classification, China Science Press, 2008(Chinese)outline
  • [3]
    Xizhao Wang, Minghu Ha, Learning from fuzzy examples and fuzzy control, Hebei University Press, 2002(Chinese)
  • [2]
    Xizhao Wang, Probability Theory and Mathematical Statistics, China Science Press, 2009(Chinese)outline
  • [1]
    Xizhao Wang, Hao Chen, Yan Zhan, Database theory and its application, Hebei People's Press, 2005(Chinese)

English Journal

  • Authors - Paper Title - Journal - Month/Year - Volume/Issue/Pages - Citation numbers (SCI/WOS/GoogleScholar)
  • [116]
    Laizhong Cui, Chong Xu, Shu Yang, Joshua Zhexue Huang, Jianqiang Li, Xizhao Wang, Zhong Ming, Nan Lu, IEEE Internet of Things Journal, 2018, DOI 10.1109/JIOT.2018.2869226
  • [115]
    Huang Z, Wang X. Sensitivity of data matrix rank in non-iterative training. Neurocomputing 313(2018) 386–391,doi:10.1016/j.neucom.2018.06.055
  • [114]
    Yichao He, Xizhao Wang⁎⁠, Group theory-based optimization algorithm for solving knapsack problems, Knowledge-Based Systems, August 2018, doi:10.1016/j.knosys.2018.07.045
  • [113]
    Laizhong Cui,Kai Zhang,Genghui Li,XiZhao Wang,Shu Yang,A smart artificial bee colony algorithm with distance-fitness-based neighbor search and its application, Information Sciences,Futur Generation Computer Systems, June 2018, Vol.89, pp.478-493, doi:10.1016/j.future.2018.06.054
  • [112]
    Junhai Zhai, Xizhao Wang, Sufang Zhang, Shaoxing Houd, Tolerance rough fuzzy decision tree, Information Sciences, October 2018, Vol. 465, pp.425-438, doi: 10.1016/j.ins.2018.07.006
  • [111]
    Zhiqi Huang, Xizhao Wang, Sensitivity of Data Matrix Rank in Non-iterative Training, Neurocomputing (2018), doi: 10.1016/j.neucom.2018.06.055
  • [110]
    Xiaojun Chen, Wenya Sun, Bo Wang, Zhihui Li, Xizhao Wang, and Yunming Ye, Spectral Clustering of Customer Transaction Data With a Two-Level Subspace Weighting Method, IEEE Transactions on Cybernetics (2018)
  • [109]
    Wing W. Y. Ng, Jianjun Zhang, Chun Sing Lai*, Witold Pedrycz, Loi Lei Lai*, and Xizhao Wang, Cost-Sensitive Weighting and Imbalance-Reversed Bagging for Streaming Imbalanced and Concept Drifting in Electricity Pricing Classification, IEEE Transactions on Industrial Informatics (2018) DOI: 10.1109/TII.2018.2850930
  • [108]
    Wing W.Y. Ng, Xing Tian, Witold Pedrycz, Xizhao Wang,Daniel S. Yeung, Incremental Hash-bit Learning for Semantic Image Retrieval in Non-stationary Environments, IEEE Transactions on Cybernetics, June 2018, PP(99):1-15, DOI: 10.1109/TCYB.2018.2846760
  • [107]
    Xizhao Wang and Weipeng Cao, Non-iterative approaches in training feed-forward neural networks and their applications, Soft Computing, 2018, https://doi.org/10.1007/s00500-018-3203-0 (0/0/0)
  • [106]
    Zhao, S-X., Wang, X-Z., Wang, L-Y., Hu, J-M. and Li, W-P. (2017), Analysis on fast training speed of extreme learning machine and replacement policy, Int. J. Wireless and Mobile Computing, Vol. 13, No. 4, pp.314–322 (0/0/0)
  • [105]
    Wing W.Y. Ng, Xiancheng Zhou, Xing Tian(*), Xizhao Wang, Daniel S. Yeung, Bagging–boosting-base d semi-supervise d multi-hashing with query-adaptive re-ranking, Neurocomputing 275 (2018) 916-923, January 2018 (0/0/1)
  • [104]
    Patrick P. K. Chan, et al, Face Liveness Detection Using a Flash Against 2D Spoofing Attack; IEEE Transactions on Information Forensis and Security; February 2018; 13(2):521-534, DOI: 10.1109/TIFS.2017.2758748 (0/0/0)
  • [103]
    Xizhao Wang, Ran Wang(*), Chen Xu, Discovering the Relationship Between Generalization and Uncertainty by Incorporating Complexity of Classification, IEEE Transactions on Cybernetics, February 2018, 48(2):703-715, DOI: 10.1109/TCYB.2017.2653223 (0/0/11)
  • [102]
    Hong Zhu, Yichao He, Xizhao Wang(*), et al, Discrete differential evolutions for the discounted {0–1} knapsack problem, Int. J. Bio-Inspired Computation, August 2017, 10(4): 219–238, DOI: 10.1504/IJBIC.2017.10008802 (1/1/9)
  • [101]
    Weipeng Cao, Xizhao Wang(*), Zhong Ming, Jinzhu Gao, A Review on Neural Networks with Random Weights, Neurocomputing 275 (2018) 278–287, Jannuary 2018, DOI: 10.1016/j.neucom.2017.08.040 (0/0/8)
  • [100]
    Yichao He, Haoran Xie, Tak-Lam Wong, Xizhao Wang (*), A novel binary artificial bee colony algorithm for the set-union knapsack problem, Future Generation Computer Systems, January 2018, 78: 77-86, DOI: 10.1016/j.future.2017.05.044 (1/1/7)
  • [99]
    Zhi Wang and Xizhao Wang, A deep stochastic weight assignment network and its application to chess playing, Journal of Parallel and Distributed Computing, July 2018, Volume 117, Pages 205-211, https://doi.org/10.1016/j.jpdc.2017.08.013 (0/0/2)
  • [98]
    Changzhong Wang(*), Qinghua Hu, Xi-Zhao Wang, et al, Feature selection based on neighborhood discrimination index, IEEE Transactions on Neural Networks and Learning Systems, June 2017, DOI: 10.1109/TNNLS.2017.2710422 (0/0/9)
  • [97]
    Ran Wang, Xi-zhao Wang (*), Sam Kwong, et al, Incorporating Diversity and Informativeness in Multiple-Instance Active Learning, IEEEE Transactions on Fuzzy Systems, December 2017, 25(6): 1460-1475, DOI: 10.1109/TFUZZ.2017.2717803 (0/0/12)
  • [96]
    Xizhao Wang, Tianlun Zhang, Ran Wang(*), Non-Iterative Deep Learning: Incorporating Restricted Boltzmann Machine into Multilayer Random Weight Neural Networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems, May 2017, PP(99) IEEE Early Access Articles, DOI: 10.1109/TSMC.2017.2701419 (0/0/12)
  • [95]
    Rana Aamir Raza Ashfaq, Xi-Zhao Wang (*), Impact of fuzziness categorization on divide and conquer strategy for instance selection, Journal of Intelligent and Fuzzy Systems, March 2017, 33(3): 1007-1018, DOI:10.3233/JIFS-162297 (0/0/4)
  • [94]
    Hongyu Zhu, Xi-Zhao Wang (*), A cost-sensitive semi-supervised learning model based on uncertainty, Neurocomputing, August 2017, 251: 106–114, DOI: 10.1016/j.neucom.2017.04.010 (0/0/4)
  • [93]
    Hong Zhu, Eric Tsang(*), Xizhao Wang, Rana Aamir Raza Ashfaq, Monotonic classification Extreme Learning Machine, Neurocomputing, February 2017, 225: 205–213, DOI: 10.1016/j.neucom.2016.11.021 (3/4/6)
  • [92]
    Weipeng Cao, Zhong Ming(*), Xizhao Wang and Shubin Cai, Improved Bidirectional Extreme Learning Machine Based on Enhanced Random Search, Memetic Computing, 2017 :1-8, DOI:10.1007/s12293-017-0238-1 (0/0/0)
  • [91]
    Mingwen Shao, Yee Leung, Xizhao Wang, et al, Granular reducts of formal fuzzy contexts, Knowledge-Based Systems, October 2016, 114:156-166, DOI: 10.1016/j.knosys.2016.10.010 (3/5/6)
  • [90]
    Rana Aamir Raza Ashfaq, Xi-Zhao Wang(*), Joshua Zhexue Huang, et al, Fuzziness based semi-supervised learning approach for intrusion detection system, Information Sciences, February 2017, 378: 484–497, DOI: 10.1016/j.ins.2016.04.019 (49/49/106)
  • [89]
    JinhaiLi(*), Cherukuri, Aswani Kumar, ChanglinMei, XizhaoWang, Comparison of reduction in formal decision contexts, International Journal of Approximate Reasoning, January 2017, 80: 100–122, DOI: 10.1016/j.ijar.2016.08.007 (7/8/19)
  • [88]
    Hong-Jie Xing(*), Xi-Zhao Wang, Selective ensemble of SVDDs with Renyi entropy based diversity measure, Pattern Recognition, January 2017, 61: 185-196. DOI: 10.1016/j.patcog.2016.07.038 (2/2/2)
  • [87]
    Junhai Zhai(*), Xizhao Wang, Xiaohe Pang, Voting-based Instance Selection from Large Data Sets with MapReduce and Random Weight Networks, Information Sciences, November 2016, 367: 1066–1077, DOI: 10.1016/j.ins.2016.07.026 (10/10/16)
  • [86]
    Weihua Xu(*), Mengmeng Li, Xizhao Wang, Information Fusion Based on Information Entropy in Fuzzy Multi-source Incomplete Information System, International Journal of Fuzzy Systems, August 2017, 19(4): 1200-1216, DOI 10.1007/s40815-016-0230-9 (2/2/5)
  • [85]
    Yi-Chao He, Xi-zhao Wang(*), Yu-Lin He, et al, Exact and approximate algorithms for discounted {0-1} knapsack problem, Information Sciences, November 2016, 369: 634–647, DOI: 10.1016/j.ins.2016.07.03 (2/4/15)
  • [84]
    Xizhao Wang(*), Yulin He, Learning from Uncertainty for Big Data (Future Analytical Challenges and Strategies), IEEE Systems, Man, & Cybernetics Magazine, April 2016, 2(2): 26-31, DOI: 10.1109/MSMC.2016.2557479 (0/0/14)
  • [83]
    Junhai Zhai(*), Ta Li, Xizhao Wang, A cross-selection instance algorithm, Journal of Intelligent & Fuzzy Systems, April 2016, 31(2): 717–728, DOI:10.3233/IFS-151792 (1/2/5)
  • [82]
    Yu-Lin He, Xi-zhao Wang(*), Joshua Zhexue Huang, Fuzzy nonlinear regression analysis using a random weight network, Information Sciences, October 2016, 364-365: 222-240, DOI: 10.1016/j.ins.2016.01.037 (58/58/82)
  • [81]
    Huanyu Zhao, Zhaowei Dong, Tongliang Li(*), Xizhao Wang, Chaoyi Pang, Segmenting time series with connected lines under maximum error bound, Information Sciences, June 2015, 345:1-8, DOI: 10.1016/j.ins.2015.09.017 (3/3/6)
  • [80]
    Xi-zhao Wang(*), Rana Aamir and Ai-Min Fu, Fuzziness based sample categorization for classifier performance improvement, Journal of Intelligent & Fuzzy Systems , June 2015, 29(3): 1185–1196, DOI:10.3233/IFS-151729 (89/90/127)
  • [79]
    Xi-zhao Wang(*), Hong-Jie Xing, Yan Li, et al, A Study on Relationship between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning,IEEE Transactions on Fuzzy Systems, October 2015, 23(5): 1638-1654, DOI:10.1109/TFUZZ.2014.2371479 (78/79/114)
  • [78]
    Yu-lin He(*), James N.K. Liu, Yan-xing Hu, Xi-zhao Wang, OWA operator based link prediction ensemble for social network, Expert Systems with Applications, January 2015, 42: 21-50, DOI: 10.1016/j.eswa.2014.07.018 (46/53/64)
  • [77]
    Yu-lin He(*), Joshua Zhexue Huang, Xi-zhao Wang, Rana Aamir Raza Ashfaq, Use Correlation Coefficients in Gaussian Process to Train Stable ELM Models, PAKDD 2015, Lecture Notes in Computer Science, 2015, 9077: 405-417, DOI: 10.1007/978-3-319-18038-0_32 (0/0/1)
  • [76]
    Ran Wang(*), Sam Kwon, Xi-zhao Wang, Qing-Shan Jiang, Segment Based Decision Tree Induction with Continuous Valued Attributes, IEEE Transactions on Cybernetics, July 2015, 45(7): 1262-1275, DOI:10.1109/TCYB.2014.2348012 (25/26/34)
  • [75]
    Xi-zhao Wang(*), Zhe-Xue Huang, Editorial: Uncertainty in learning from big data, Fuzzy Sets and Systems, January 2015, 258: 1-4, DOI: 10.1016/j.fss.2014.10.010 (9/9/20)
  • [74]
    Xi-zhao Wang(*), Learning from big data with uncertainty-editorial, Journal of Intelligent and Fuzzy Systems, October 2015, 28(5): 2329-2330, DOI:10.3233/IFS-141516 (77/77/48)
  • [73]
    Shuxia Lu(*), Xi-zhao Wang, Guiqiang Zhanga and Xu Zhoua, Effective algorithms of the Moore-Penrose inverse matrices for extreme learning machine, Intelligent Data Analysis, Augest 2015, 19(4): 743–760, DOI 10.3233/IDA-150743 (39/40/44)
  • [72]
    Yulin He(*), Ran Wang, Sam Kwong, Xizhao Wang, Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis, Information Sciences, February 2014, 259(3):252-268.(23/28/38)
  • [71]
    Xi-zhao Wang, Abdallah Bashir Musa(*), Advances in neural network based learning, International Journal of Machine Learning and Cybernetics, February 2014, 5(1): 1-2, DOI: 10.1007/s13042-013-0220-2 (8/8/9)
  • [70]
    Xi-zhao Wang(*), Ran Wang, Hui-Min Feng, Huachao Wang, A new approach to classifier fusion based on upper integral, IEEE Transactions on Cybernetics, March 2014, 44(5): 620-635, DOI: 10.1109/TCYB.2013.2263382 (16/16/27)
  • [69]
    Xi-zhao Wang(*), Yu-Lin He, Dabby D. Wang, Non-Naive Bayesian Classifiers for Classification Problems with Continuous Attributes, IEEE Transactions on Cybernetics, January 2014, 44(1): 21-39, DOI: 10.1109/TCYB.2013.2245891 (32/35/58)
  • [68]
    Huimin Feng and Xizhao Wang(*), Performance Improvement of Classifier Fusion for Batch Samples Based on Upper Integral, Neural Networks, March 2015, pp. 87-93, DOI: 10.1016/j.neunet.2014.11.004 (4/4/5)
  • [67]
    Chunru Dong, Wing W.Y. Ng(*), Xizhao Wang, et al, An improved differential evolution and its application to determining feature weights in similarity-based Clustering, Neurocomputing, December 2014, 146: 95-103, DOI: 10.1016/j.neucom.2014.04.065 (5/5/14)
  • [66]
    Aimin Fu, Xizhao Wang, Yulin He(*), Laisheng Wang, A study on residence error of training an extreme learning machine and its application to evolutionary algorithms, Neurocomputing, December 2014, 146(1): 75-82, DOI: 10.1016/j.neucom.2014.04.067 (6/6/8)
  • [65]
    Hongyan Ji, Xizhao Wang(*), Yulin He, Wenliang Li, A study on relationships between heuristics and optimal cuts in decision tree induction, Computers and Electrical Engineering, July 2014, 40: 1429-1438, DOI: 10.1016/j.compeleceng.2013.11.030 (0/0/0)
  • [64]
    James N. K. Liu(*), Yulin He, Edward H. Y. Lim, Xizhao Wang, Domain ontology graph model and its application in Chinese text classification, Neural Computing and Applications, March 2014, 24(3-4): 779-798, DOI: 10.1007/s00521-012-1272-z (1/1/15)
  • [63]
    Xi-zhao Wang(*), Hui Wang, Guest editorial: learning from uncertainty and its application to intelligent systems of web information, World Wide Web-internet Web Information Systems, September 2014, 17(5): 1027-1028, DOI: 10.1007/s11280-013-0255-z (0/0/0)
  • [62]
    Lisha Hu(*), Shuxia Lu, Xizhao Wang, A New and Informative Active Learning Approach for Support Vector Machine, Information Sciences, September 2013, 244: 142-160, DOI: 10.1016/j.ins.2013.05.010 (10/13/14)
  • [61]
    Suyun Zhao(*), Xizhao Wang, Degang Chen and Eric Tsang, Nested structure in parameterized rough reduction, November 2013, 248: 130-150, DOI: 10.1016/j.ins.2013.05.039 (21/21/22)
  • [60]
    Xizhao Wang(*), Qingyan Shao, Miao Qing, Junhai Zhai, Architecture selection for networks trained with extreme learning machine using localized generalization error model, Neurocomputing, February 2013, 102: 3-9, DOI: 10.1016/j.neucom.2011.11053 (49/50/40)
  • [59]
    Xizhao Wang(*), Lingcai Dong, Jianhui Yan, Maximum ambiguity based sample selection in fuzzy decision tree induction, IEEE Transactions on Knowledge and Data Engineering, August 2012, 24(8): 1491-1505, DOI: 10.1109/TKDE.2011.67 (96/100/136)
  • [58]
    Qiang Hua(*), Lijie Bai, and Xizhao Wang, Local similarity and diversity preserving discriminant projection for face and handwriting digits recognition, NeuroComputing, June 2012, 86:150-157, DOI: 10.1016/j.neucom.2012.01.031 (7/8/9)
  • [57]
    Yulin He(*), James N. K. Liu, Xizhao Wang, et al, Optimal bandwidth selection for re-substitution entropy estimation, Applied Mathematics andComputation, December 2012, 219(8): 3425-3460, DOI: 10.1016/j.amc.2012.08.056 (3/3/7)
  • [56]
    Xizhao Wang(*), Yulin He, Lingcai Dong, et al, Particle swarm optimization for determining fuzzy measures from data, Information Sciences, October 2011, 181(19): 4230-4252, DOI: 10.1016/j.ins.2011.06.002 (84/87/110)
  • [55]
    Xizhao Wang(*), Aixia Chen, Huimin Feng, Upper integral network with extreme learning mechanism, Neurocomputing, September 2011, 74(16): 2520-2525, DOI: 10.1016/j.neucom.2010.12.034 (70/70/88)
  • [54]
    Suyun Zhao(*), Eric C. C. Tsang, Degang Chen, Xizhao Wang, Building a rule-based classifier-a fuzzy-rough set approach, IEEE Transactions on Knowledge and Data Engineering, May 2010, 22(5): 624-638, DOI: 10.1109/TKDE.2009.118 (59/65/104)
  • [53]
    Xizhao Wang(*), Chunru Dong, Improving generalization of fuzzy if-then rules by maximizing fuzzy entropy, IEEE Transactions on Fuzzy Systems, June2009, 17(3): 556-567, DOI: 10.1109/TFUZZ.2008.924342 (141/141/184)
  • [52]
    Xizhao Wang(*), Junhai Zhai, Shuxia Lu, Induction of multiple fuzzy decision trees based on rough set technique, Information Sciences, August 2008, 178(16): 3188-3202, DOI: 10.1016/j.ins.2008.03.021 (113/119/154)
  • [51]
    Xizhao Wang(*), Chunguo Li, A Definition of Partial Derivative of Random Functions and Its Application to RBFNN Sensitivity Analysis, Neurocomputing, March 2008, 71(7-9): 1515-1526, DOI: 10.1016/j.neucom.2007.05.005 (10/10/22)
  • [50]
    Ng Wing(*), DS. Yeung, M Firth, ECC Tsang, Xizhao Wang, Feature Selection Using Localized Generalization Error for Supervised Classification Problems Using RBFNN, Pattern Recognition, December 2008, 41(12): 3706-3719, DOI: 10.1016/j.patcog.2008.05.004 (30/33/74)
  • [49]
    Xizhao Wang(*), Junhai Zhai, Sufang Zhang, A model of finite-step random walk with absorbent boundaries, International Journal of Computer Mathematics, 2008, 85(11):1685-1696, DOI: 10.1080/00207160701543400 (0/0/2)
  • [48]
    Xizhao Wang(*), Shuxia Lu, Junhai Zhai, Fast fuzzy multicategory SVM based on support vector domain description, International Journal of Pattern Recognition and Artificial Intelligence, February 2008, 22(1): 109-120, DOI: 10.1142/S0218001408006144 (34/34/44)
  • [47]
    Xizhao Wang(*), Feng Guo, Xianghui Gao, Task 2 winner's solution: A Minkowski distance and nearest-unlike-neighbor distance method, within the paper “ Qiang Yang, et al, Estimating location using Wi-Fi”, IEEE Intelligent Systems, 2008, 23(1): 8-13 (31/31/112)
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    Daniel Yeung(*), Shuyuan Jin, Xizhao Wang, Covariance-matrix modeling and detecting various flooding attacks, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, March 2007, 37(2): 157-169, DOI: 10.1109/TSMCA.2006.889480 (27/27/57)
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    DS Yeung(*), Ng Wing, Defeng Wang, Eric Tsang, Xizhao Wang, Localized generalization error model and its application to architecture selection for radial basis function neural network, IEEE Transactions on Neural Networks, September 2007, 18(5): 1294-1305, DOI: 10.1109/TNN.2007.894058 (75/78/150)
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    Xizhao Wang(*), Eric Tsang, Suyun Zhao, Degang Chen, Daniel Yeung, Learning fuzzy rules from fuzzy examples based on rough set techniques, Information Sciences, 2007, 177(20): 4493-4514 (112/116/161)
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    Xizhao Wang(*), Chunru Dong, Tiegang Fan, Training T-S norm neural networks to refine weights for fuzzy if-then rules, Neurocomputing, August 2007, 70(13-15): 2581-2587, DOI: 10.1016/j.neucom.2007.01.005 (29/31/40)
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    Degang Chen(*), Qiang He, Xizhao Wang, On Linear Separability of Data Sets in Feature Space, Neurocomputing, August 2007, 70(13): 2441-2448, DOI: 10.1016/j.neucom.2006.12.002 (13/14/25)
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    Shuyuan Jin(*), DS Yeung, Xizhao Wang, Network Intrusion Detection in Covariance Feature Space, Pattern Recognition, August 2007, 40(8): 2185-2197, DOI: 10.1016/j.patcog.2006.12.010 (23/24/100)
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    Xizhao Wang(*),Sufang Zhang, Junhai Zhai, A nonlinear integral defined on partition and its application to decision trees, Soft Computing, February 2007, 11(4): 317-321, DOI: 10.1007/s00500-006-0083-5 (7/7/7)
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    Yan Li(*), Xizhao Wang, Minghu Ha, An on-line Multi-CBR agent dispatching algorithm, Soft Computing, June 2007, 11(1): 1-5, DOI: 10.1007/s00500-005-0032-8 (1/1/1)
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    DS Yeung(*), Defeng Wang, Ng Wing, Eric Tsang, Xizhao Wang, Structured large margin machines: sensitive to data distribution, Machine Learning, August 2007, 68(2): 171-200, DOI: 10.1007/s10994-007-5015-9 (47/47/60)
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    Ng Wing(*), DS Yeung, De-Feng Wang, Eric Tsang, Xizhao Wang, Localized generalization error of Gaussian-based classifiers and visualization of decision boundaries, Soft Computing, February 2007, 11(4): 375-381, DOI: 10.1007/s00500-006-0092-4 (4/4/12)
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    Shuyuan Jin(*), DS Yeung, Xizhao Wang, Internet anomaly detection based on statistical covariance matrix, International Journal of Pattern Recognition and Artificial Intelligences, May 2007, 21(3): 591-606, DOI: 10.1142/S0218001407005557 (0/0/1)
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    Xizhao Wang(*), Jun Shen, Using special structured fuzzy measure to represent interaction among IF-THEN rules, Lecture Notes in Artificial Intelligence, 2006, 3930: 459-466 (1/1/3)
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    Qiang He(*), Xizhao Wang, Junfen Chen, et al, A parallel genetic algorithm for solving the inverse problem of support vector machines, Lecture Notes in Artificial Intelligence, 2006, 3930: 871-879 (1/1/3)
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    John W. T. Lee(*), Xizhao Wang, Jinfeng Wang, Reduction of attributes in ordinal decision systems, Lecture Notes in Artificial Intelligence, 2006, 3930: 578-587(0/0/1)
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    Shuyuan Jin(*), DS Yeung, Xizhao Wang, et al, A covariance matrix based approach to Internet anomaly detection, Lecture Notes in Artificial Intelligence, 2006, 3930: 691-700 (0/0/4)
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    Degang Chen(*), Qiang He, Chunru Dong, Xizhao Wang, A method to construct the mapping to the feature space for the dot product kernels, Lecture Notes in Artificial Intelligence, 2006, 3930: 918-929 (0/0/1)
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    DS Yeung(*), Degang Chen, ECC Tsang, JWT Lee, Xizhao Wang, On the generalization of fuzzy rough sets, IEEE Transactions on Fuzzy Systems, June 2005, 13(3): 343-361, DOI: 10.1109/TFUZZ.2004.841734 (214/230/351)
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    Xizhao Wang(*), Qiang He, Degang Chen, Daniel Yeung, A genetic algorithm for solving the inverse problem of support vector machines, Neurocomputing, October 2005, 68: 225-238, DOI: 10.1016/j.neucom.2005.05.006 (53/54/66)
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    Degang Chen(*), ECC Tsang, DS Yeung, Xizhao Wang, The parameterization reduction of soft sets and its applications, Computers & Mathematics with Applications, APR-MAY 2005, 49(5-6): 757-763, DOI: 10.1016/j.camwa.2004.10.036 (294/326/626)
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    Xizhao Wang(*), Chunguo Li, A new definition of sensitivity for RBFNN and its applications to feature reduction, Lecture Notes in Computer Science, 2005, 3496: 81-86 (12/12/13)
  • [26]
    Degang Chen(*), Qiang He, Xizhao Wang, The infinite polynomial kernel for support vector machine, Lecture Notes in Artificial Intelligence, 2005, 3584: 267-275 (2/2/5)
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    Caihong Sun(*), S. C. K. Shiu, Xizhao Wang, Organizing large case library by linear programming, Lecture Notes in Artificial Intelligence, November 2005, 3789: 554-564 (0/0/0)
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    ECC Tsang(*), Xizhao Wang, An approach to case-based maintenance: Selecting representative cases, International Journal of Pattern Recognition and Artificial Intelligence, February 2005, 19(1): 79-89, DOI: 10.1142/S0218001405003909 (2/2/6)
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    DS Yeung(*), Xizhao Wang, ECC Tsang, Handling interaction in fuzzy production rule reasoning, IEEE Transactions on Systems, Man, and Cybernetics, Part B-Cybernetics, October 2004, 34(5): 1979-1987, DOI: 10.1109/TSMCB.2004.831460 (13/14/40)
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    ECC Tsang(*), DS Yeung, JWT Lee, DM Huang, Xizhao Wang, Refinement of generated fuzzy production rules by using a fuzzy neural network, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, February 2004, 34(1): 409-418, DOI: 10.1109/TSMCB.2003.817033 (16/17/27)
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    Xizhao Wang(*), Yadong Wang, Lijuan Wang, Improving fuzzy c-means clustering based on feature-weight learning, Pattern Recognition Letters, July 2004, 25(10): 1123-1132, DOI: 10.1016/j.patrec.2004.03.008 (155/192/324)
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    Xizhao Wang(*), Qiang He, Enhancing generalization capability of SVM classifiers with feature weight adjustment, Lecture Notes in Computer Science, 2004, 3213: 1037-1043 (9/9/19)
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    ECC Tsang(*), DS Yeung, Xizhao Wang, OFFSS: Optimal fuzzy-valued feature subset selection, IEEE Transactions on Fuzzy Systems, April 2003, 11(2): 202-213, DOI: 10.1109/TFUZZ.2003.809895 (31/32/61)
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    Minghu Ha(*), Xizhao Wang, Lanzhen Yang, et al, Sequences of (S) fuzzy integrable functions, Fuzzy Sets and Systems, September 2003, 138 (3): 507-522, DOI: 10.1016/S0165-0114(02)00363-9 (5/5/11)
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    Xizhao Wang(*), Minghua Zhao, Dianhui Wang, Selection of parameters in building fuzzy decision trees, Lecture Notes in Artificial Intelligence, 2003, 2903: 282-292 (0/0/2)
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    DS Yeung(*), Xizhao Wang, Improving performance of similarity-based clustering by feature weight learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, April 2002, 24(4): 556-561, DOI: 10.1109/34.993562 (59/72/103)
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    Xizhao Wang(*), DS Yeung, ECC Tsang, A comparative study on heuristic algorithms for generating fuzzy decision trees, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, April 2001, 31(2): 215-226, DOI: 10.1109/3477.915344 (80/84/156)
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    Xizhao Wang(*), Zimian Zhong, Minghu Ha, Iteration algorithms for solving a system of fuzzy linear equations, Fuzzy Sets and Systems, April 2001, 119(1):121-128, DOI: 10.1016/S0165-0114(98)00284-X (44/48/83)
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    Xizhao Wang(*), Yadong Wang, X F Xu, et al, A new approach to fuzzy rule generation: fuzzy extension matrix, Fuzzy Sets and Systems, November 2001, 123(3): 291-306, DOI: 10.1016/S0165-0114(01)00002-1 (39/40/62)
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    S. C. K. Shiu(*), Caihung Sun, Xizhao Wang, et al, Maintaining Case-Based Reasoning systems using fuzzy decision trees, Lecture Notes in Artificial Intelligence, 2001, 1898: 285-296 (0/0/42)
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    Guoqing Cao(*), Simon Shiu, Xizhao Wang, A fuzzy-rough approach for case base maintenance, Lecture Notes in Artificial Intelligence, 2001, 2080: 118-130 (7/7/25)
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    Simon C. K. Shiu(*), Daniel S. Yeung, Caihung Sun, Xizhao Wang, Transferring case knowledge to adaptation knowledge: An approach for case-base maintenance, Computational Intelligence, May 2001, 17(2): 295-314 (26/29/78)
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    ECC Tsang(*), Xizhao Wang, DS Yeung, Improving learning accuracy of fuzzy decision trees by hybrid neural networks, IEEE Transactions on Fuzzy Systems, October 2000, 8(5): 601-614, DOI: 10.1109/91.873583 (53/54/70)
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    Xizhao Wang(*), Jiarong Hong, Learning optimization in simplifying fuzzy rules, Fuzzy Sets and Systems, September 1999, 106(3): 349-356,DOI: 10.1016/S0165-0114(97)00300-X (43/44/66)
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    Xizhao Wang, Minghu Ha(*), Note on maxmin mu/E estimation, Fuzzy Sets and Systems, 1998, 94(1): 71-75 (2/7/*)
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    Minghu Ha(*), Xizhao Wang, Congxin Wu, Fundamental convergence of sequences of measurable functions on fuzzy measure space, Fuzzy Sets and Systems, April 1998, 95(1): 77-81 (10/13/17)
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    Minghu Ha(*), Lixin Cheng, Xizhao Wang, Notes on Riesz's theorem on fuzzy measure space, Fuzzy Sets and Systems, September 1997, 90(3): 361-363 (3/5/5)
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    Minghu Ha(*), Xizhao Wang, Some notes on the regularity of fuzzy measures on metric spaces, Fuzzy Sets and Systems, May 1997, 87(3): 385-387, DOI: 10.1016/S0165-0114(96)00161-3 (7/7/16)
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    Xizhao Wang(*), Minghu Ha, Fuzzy linear regression analysis, Fuzzy Sets and Systems, October 1992, 51(2): 179-188 (7/9/31)

Chinese Journal

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    He YC, Wang XZ, Zhao SL, Zhang XL. Design and applications of discrete evolutionary algorithms based on encoding transformation. Ruan Jian Xue Bao/Journal of Software, 2018,29(9) (in Chinese)
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    Wang Xi-Zhao, He Yi-Chao. Evolutionary Algorithms for Knapsack Problems.Journal of Software,2017,281(1): 1-16. doi: 10.13328/j.cnki.jos.005139.
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    He Yi-Chao, Wang Xi-Zhao, Li Wen-Bin. Exact Algorithms and Evolutionary Algorithms for Randomized Time-Varying Knapsack Problem[J].Journal of Software,2017, 28(02):185-202.doi: 10.13328/j.cnki.jos.004937.
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    Wang Xi-Zhao, Xing-Sheng, Zhao Shi-Xin. Big Data Classification Sample Selection Mechanism Based on Nonstationary Cutoffs.Pattern Recognition and Artificial Intelligence,Hiring,2016
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    Xing-Sheng, Wang Xi-Zhao, Wang Xiao-Lan. Multi - class resampling based on unbalanced data speed learning Machine integrated learning.Journal of Nanjing University (Natural Science),2016, 52(1): 203-211.
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    He Yi-Chao, Wang Xi-Zhao, Li Wen-Bin. Research on Genetic Algorithms for the Discounted {0-1}Knapsack Problem.Journal of Computer,2016, 39(12):2614-2630. doi: 10.11897/SP.J.1016.2016.02614
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    He Yi-Chao, Wang Xi-Zhao, Liu Kun-Qi, Wang Yan-Qi. Convergent Analysis and Algorithmic Improvement of Differential Evolution, Journal of Software, 21(5):875-885, 2010.
  • [34]
    Wang Xi-Zhao, Yang Chen-Xiao. Merging-Branches Impact on Decision Tree Induction, Chinese Journal of Computers, 30(8):1251-1258, 2007.
  • [33]
    Wang Xi-Zhao, An Su-Fang. Research on Learning Weights of Fuzzy Production Rules Based on Maximum Fuzzy Entropy, Journal of Computer Research and Development, 43(4):673-678, 2006. [EI]
  • [32]
    Wang Xi-Zhao, Zhao Su-Yun, and Wang Jing-Hong. Simplification of Information Table with Fuzzy-Valued Attributes Based on Rough Sets, Journal of Computer Research and development, 41(11): 1974-1981, 2004. [EI]
  • [31]
    Wang Xi-Zhao, Zhao Su-Yun. Modelling Fuzzy Rough Sets Based on Similarity Relation, Computer Science, 31(10)A: 31-35, 2004.
  • [30]
    Wang Xi-Zhao, Wang Ya-Dong, Zhan Yan, and Yuan Fang. Optimization of K-means Clustering by Feature Weight Learning, Journal of Computer Research and Development, 40(6):869-873, 2003.
  • [29]
    Ha Ming-Hu, Wang Xi-Zhao, Yan Li, and Tian Da-Zeng. Principles of Fuzzy Controller Based on Example Learning, Journal of Hebei University, 20(2): 116-121, 2000.
  • [28]
    Wang Xi-Zhao, Ling Wei-De, A Comparison of Two Heuristics for Fuzzy Decision Tree Generation, 20(1):1-6, 2000.
  • [27]
    Huang Dong-Mei, Ha Ming-Hu, Wang Xi-Zhao. Comparison Between Decision Tree and Fuzzy Decision Tree, Journal of Hebei University, 20(3): 218-221, 2000
  • [26]
    Ye Feng, Quan Guang-Ri, Wang Xi-Zhao, Resolution Based Most General Specialization of Theory, Chinese Journal of Computers, 22(12): 1233-1238, 1999
  • [25]
    Huang Dong-Mei, Wang Xi-Zhao. An Improved Interval-valued Decision Tree Algorithm, Journal of Hebei University, 19(4): 325-328, 1999.
  • [24]
    Wang Xi-Zhao, Hong Jia-Rong, Learning Algorithm of Decision Tree Generation for Interval-Valued Attributes, Journal of Software, 9(8): 637-640, 1998.
  • [23]
    Qian Guo-Liang, Wang Xi-Zhao, Chen Bin. Fuzzy Inductive Learning for Feature Extraction of Hand-Written Chinese Characters, Journal of Tsinghua University, 38 (S2): 85-88, 1998.
  • [22]
    Sun Jian-Ping, Zhang Yan-e, Wang Xi-Zhao, The Solution and Properties of Fuzzy Matrix Equations, Fuzzy Systems and Mathematics, 12(4):72-78, 1998.
  • [21]
    Zhong Zi-Mian, Wang Hao, Wang Xi-Zhao, A Fuzzy Learning Algorithm with Expert's Knowledge and Its Application to Reservoir Identification, Journal of Hebei University, 18(3): 215-218, 1998.
  • [20]
    Wang Xi-Zhao, Representation Theory of Imprecise Concepts Part (II)-Reduction and Dependence of Knowledge, Journal of Hebei University, 17(2): 1-5, 1997.
  • [19]
    Wang Xi-Zhao, Representation Theory of Imprecise Concepts Part (I)-Concepts and Basic Knowledge, Journal of Hebei University, vol. 4, pp. 1-6, 1996.
  • [18]
    Wang Xi-Zhao, Ha Ming-Hu, Shi Guang-Ben. A New Type of Fuzzy Regression Model, Journal of Lanzhou University, vol. 32, pp. 472-475, 1996.
  • [17]
    Liu Huijie, Wang Xi-Zhao, A Fuzzy Example Learning Model and the Decision Tree Algorithm, Hebei University, 1996, pp. 1-4.
  • [16]
    Ha Minghu, Wang Xi-Zhao, Shi Guangben. On the Pseudo Null-additivity and Pseudo-autocontinuity of Fuzzy Measures, Journal of Lanzhou University, vol. 32, pp. 136-139, 1996.
  • [15]
    Wang Xi-Zhao, Shi Guangben. Variable Selection in Fuzzy Regression, Fuzzy Systems and Mathematics, vol. 8, 1994, pp. 66-68
  • [14]
    Wang Xi-Zhao, Ha Minghu. A Type of Fuzzy Distance and Its Application in Regression Analysis, Hebei University, vol. 4, 1994, pp. 8-13 .
  • [13]
    Wang Xi-Zhao, Ha Minghu. Iterative Algorithms for Solving a Type of Fuzzy Linear Equations, In Theories and Applications of Fuzzy Analysis and Design, (edited by Wang Caihua et al. China Architecture and Building Press, 1993) pp. 604-605
  • [12]
    Wang Xi-Zhao, Ha Minghu. Multi-variable Fuzzy Linear Regression, Journal of Hebei University, vol. 3, 1993, pp. 8-14
  • [11]
    Wang Xi-Zhao, Ha Minghu, Pan-Fuzzy Integrals, Journal of Hebei University, vol. 3, 1992, pp. 18-24
  • [10]
    Wang Xi-Zhao, Ha Minghu. Non-Linear Fuzzy Model Analysis and Parameter Estimation, Fuzzy Systems and Mathematics, vol. 6, 1992, pp. 38-41
  • [9]
    Wang Xi-Zhao, Ha Minghu, Ling Weide, Sequence Space of Fuzzy Values, Fuzzy Systems and Mathematics, vol. 6, 1992, pp. 41-43
  • [8]
    Ha Minghu, Wang Xi-Zhao, Absolute Continuitivity and Extension of Fuzzy Measures, Fuzzy Systems and Mathematics, vol. 6, 1992, pp. 35-37
  • [7]
    Wang Xi-Zhao, Ha Minghua, A Fuzzy Measure defined by Pan-Integral, Advances in Fuzzy Mathematics and Systems, (Edited by Cao Bingyuan, Hunan Science and Technology Press, 1991) pp. 61-63
  • [6]
    Ha Minghu, Wang Xi-Zhao, Fuzzy Linear Regression Analysis and Parameter Estimation, Advances in Fuzzy Mathematics and Systems, (Edited by Cao Bingyuan, Hunan Science and Technology Press, 1991) pp. 19-21
  • [5]
    Ha Minghu, Wang Xi-Zhao, Absolute Continuitivity and Extension of Fuzzy MeasuresonFuzzy sets, Journal of Hebei University, vol. 4, 1991, pp. 17-22
  • [4]
    Wang Xi-Zhao, Ha Minghu, Fuzzy Measure on σ-additivity Fuzzy Sets, Journal of Hebei University, vol. 1, 1991, pp. 17-24
  • [3]
    Wang Xi-Zhao, Ha Minghu, Fuzzy Measures and Structure Properties on sigma-additive Fuzzy Sets, Proc. Of the 5th China Conference on Fuzzy Mathematics and Fuzzy Systems, (Edits by: Xu Yang, Yu Xiaohua, Press of South-West Jiaotong University, Chendu, 1990) pp. 57-59
  • [2]
    Ha Minghua, Wang Xi-Zhao, A Parameter Estimation Method for Fuzzy-Valued Variable Linear Regressions, Journal of Hebei University, vol. 5, 1989, pp. 15-19
  • [1]
    Ha Minghu, Wang Xi-Zhao, Fuzzy Measures and Convergence, Journal of Hebei University, vol. 5, 1989, pp. 79-86

Conference papers

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    Sheng Xing(*), Hong Zhu, Yulin He, Xizhao Wang, An Approach to Sample Selection from Big Data for Classification, IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary, 09-12 October 2016, Proceedings pp: 002928-002935, DOI: 10.1109/SMC.2016.7844685
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    Jian Zhang(*), Junhai Zhai, Hong Zhu, Xizhao Wang, Induction of monotonic decision trees. Proceedings of 2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), Guangzhou, China, 12-15 July 2015, Proceedings pp: 203-207, DOI: 10.1109/ICWAPR.2015.7295951
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    Peizhou Zhang(*), Shixin Zhao, Xizhao Wang, The failure analysis of extreme learning machine on big data and the counter measure, Proceedings of 2015 International Conference on Machine Learning and Cybernetics (ICMLC), Guangzhou, China, 12-15 July 2015, Proceedings pp: 849-853, DOI: 10.1109/ICMLC.2015.7340664
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    Xin Wang(*), Junhai Zhai, Jiankai Chen, Xizhao Wang, Ordinal decision trees based on fuzzy rank entropy, Proceedings of 2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), Guangzhou, China, 12-15 July 2015, Proceedings pp. 208-213, DOI: 10.1109/ICWAPR.2015.7295952
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    Junhai Zhai(*), Jinggeng Wang, Xizhao Wang, Ensemble online sequential extreme learning machine for large data set classification, Proceedings of 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), San Diego, CA, USA, 05-08 October 2014 , Proceedings pp. 2250-2255, DOI: 10.1109/SMC.2014.6974260
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    Yan Li(*), Hongjie Xing, Qiang Hua, Xzhao Wang, Prerna Batta, Soroush Haeri, Ljiljana Trajković, Classification of BGP anomalies using decision trees and fuzzy rough sets, Proceedings of 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), San Diego, CA, USA, 05-08 October 2014, Proceedings pp. 1312-1317, DOI: 10.1109/SMC.2014.6974096
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    James N. K. Liu(*), Yanxing Hu, Yulin He, Xizhao Wang, Regression ensemble with PSO algorithms based fuzzy integral, Proceedings of 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, 06-11 July 2014, Proceedings pp. 762-768, DOI: 10.1109/CEC.2014.6900342
  • [67]
    Xizhao Wang(*), Meng Zhang, Shuxia Lu, Xu Zhou, A total error rate multi-class classification, In Proceedings of 2012 International Conference on Systems, Man, and Cybernetics, Seoul, South Korea, 14-17 October 2012, Proceedings pp: 964-969.(EI)
  • [66]
    Xizhao Wang(*), Qing Miao, Mengyao Zhai, Junhai Zhai, Instance selection based on sample entropy for efficient data classification with ELM, In Proceedings of 2012 International Conference on Systems, Man, and Cybernetics, Seoul, South Korea, 14-17 October 2012, Proceedings pp: 970-974.(EI)
  • [65]
    Hongjie Xing(*), Xizhao Wang, Minghu Ha, A comparative experimental study of feature-weight learning approaches, In Proceedings of 2011 International Conference on Systems, Man, and Cybernetics, Anchorage, AK, USA, 09-12 October 2011 , Proceedings pp: 3500-3505, DOI: 10.1109/ICSMC.2011.6084211(EI)
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    Junhai Zhai(*), Yuanyuan Gao, Mengyao Zhai, Xizhao Wang, Rough set model and its eight extensions, In Proceedings of 2011 International Conference on Systems, Man, and Cybernetics, Anchorage, AK, USA, 09-12 October 2011, Proceedings pp: 3512-3517.(EI)
  • [63]
    James N. K. Liu(*), Yulin He, Xizhao Wang, Yanxing Hu, A comparative study among different kernel functions in flexible naïve Bayesian classification, In Proceedings of 2011 International Conference on Machine Learning and Cybernetics, Guilin, China, 10-13 July 2011 Proceedings pp: 638-643.(EI)
  • [62]
    Xizhao Wang(*), Xianghui Gao, Qiang He, Side effect of cut in decision tree generation for continuous attributes, In Proceedings of 2010 International Conference on Systems, Man, and Cybernetics, Istanbul, Turkey, 10-13 October 2010, Proceedings pp: 1364-1369.(EI)
  • [61]
    Shan Su(*), Xizhao Wang, Junhai Zhai, An Improved Cluster Oriented Fuzzy Decision Trees, In Proceedings of 2009 International Conference on Rough Sets, Fuzzy Sets , Data Mining & Granular Computing, Indian Inst Technol, Delhi, India, 15-18 December 2005-2009, Proceedings pp: 447-454.(EI)
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    Ling-Cai Dong(*), Dan Wang, Xi-Zhao Wang, An Improved Sample Selection Algorithm in Fuzzy Decision Tree Induction, In Proceedings of 2009 International Conference on Systems, Man, and Cybernetics, San Antonio, TX, 11-14 October 2009 , Proceedings pp: 629-634.(EI)
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    Mingzhu Lu(*), Philip Chen, Jianbing Huo, Xizhao Wang, Multi-Stage Decision Tree based on Inter-class and Inner-class Margin of SVM, In Proceedings of 2009 International Conference on Systems, Man, and Cybernetics, San Antonio, TX, USA, 11-14 October 2009, Proceedings pp: 1875-1880.(EI)
  • [58]
    Ning Zhang(*), Xizhao Wang, Tao Xiao, An Instance Selection Algorithm Based on Contribution, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, China, 12-15 July 2008, Proceedings pp: 919-923.(EI)
  • [57]
    Feng Guo(*), Xizhao Wang, Yan Li, A New Algorithm for Solving Convex Hull Problem and Its Application to Feature Selection, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, China, 12-15 July 2008, Proceedings pp: 369-373.(EI)
  • [56]
    Xizhao Wang(*), Bo Wu, Yulin He, Xianghao Pei, NRMCS: Noise Removing Based on the MCS, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, China, 12-15 July 2008, Proceedings pp: 89-93.(EI)
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    Xizhao Wang(*), Junhai Zhai, Sufang Zhang, Fuzzy Decision Tree Based on the Important Degree of Fuzzy Attribute, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, China, 12-15 July 2008, Proceedings pp: 511-516.(EI)
  • [54]
    Mingzhu Lu(*), C. L. Philip Chen, Jianbing Huo, Xizhao Wang, Optimization of combined kernel function for SVM based on large margin learning theory, In Proceedings of 2008 International Conference on Systems, Man, and Cybernetics, Singapore, 12-15 October 2008, Proceedings pp: 353-358.(EI)
  • [53]
    Hongjie Xing(*), Xizhao Wang, Ruixian Zhu, Dan Wang, Application of kernel learning vector quantization to novelty detection, In Proceedings of 2008 International Conference on Systems, Man, and Cybernetics, Singapore, 12-15 October 2008, Proceedings pp: 439-443.(EI)
  • [52]
    Degang Chen(*), Xizhao Wang, Suyun Zhao, Attribute reduction based on fuzzy rough sets, Proceedings of the International Conference on Rough Sets and Intelligent Systems Paradigms, Warsaw, Poland, 28-30 June 2007, Rough Sets and Intelligent Systems Paradigms, Proceedings pp: 381-390.
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    Weili Zhang(*), Xizhao Wang, Feature extractionand classification for human brain CT images, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, 19-22 Augest 2007, Proceedings pp: 1155-1159.
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    Xizhao Wang(*), Weixi Lin, Application of inductive learning in human brain CT image recognition, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, 19-22 Augest 2007, Proceedings pp: 1667-1671.(EI)
  • [49]
    Xizhao Wang(*), Xiaoyan Liu, Yan Li and Chunguo Li, Norm-based localized generalization error model and its derivation for radial basis function neural networks, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, 19-22 Augest 2007, Proceedings pp: 3623-3527.(EI)
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    Xizhao Wang(*), Bin Wu, Jie Li, An improvement for localized generalization error model, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, 19-22 August, 2007, Proceedings pp: 2901-2910.(EI)
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    Xizhao Wang(*), Jianhui Yan, Ran Wang and Chunru Dong, A sample selection algorithm in fuzzy decision tree induction and its theoretical analyses, Proceedings of 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, Canada, 7-10 October 2007, Proceedings pp: 3621-3626.(EI)
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    Xizhao Wang(*), Shuxia Lu and Ruixian Zhu, Solving SVM inverse problems based on clustering, Proceedings of 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, Canada, 7-10 October 2007, Proceedings pp: 3615-3620.(EI)
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    Limei Feng(*), Xizhao Wang, Improving on symbolic learning system based on genetic algorithm, Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering, Chengdu, China, 15-16 October 2007, Proceedings pp: 1132-1138.(EI)
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    Jinyan Sun(*), Xizhao Wang, A new method for constructing radial basis function neural networks, Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering, Chengdu, China, 15-16 October 2007, Proceedings pp: 1240-1245.(EI)
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    Chenxiao Yang(*), Xizhao Wang and Ruixian Zhu, A strategy of merging branches based on margin enlargement of SVM in decision tree induction, Proceedings of 2006 IEEE International Conference on Systems, Man and Cybernetics, Taipei, China, 8-11 October 2006, Proceedings pp: 824-828.(EI)
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    Jianbing Huo(*), Xizhao Wang, Mingzhu Lu and Junfen Chen, Induction of multi-stage decision tree, Proceedings of 2006 IEEE International Conference on Systems, Man and Cybernetics, Taipei, China, 8-11 October 2006, Proceedings pp: 835-839.(EI)
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    Xizhao Wang(*) ,Xianghui Gao, A research on the relation between training ambiguity and generalization capability, Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 2008-2013.(EI)
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    Miao Wang(*), Xizhao Wang, A research on weight acquisition of weighted fuzzy production rules based on genetic algorithm, Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 2208-2211.(EI)
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    Xizhao Wang(*), Shuxia Lu, Improved fuzzy multicategory support vector machines classifier, Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 3585-3589.(EI)
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    Xizhao Wang(*), Mingzhu Lu and Jianbing Huo, Fault diagnosis of power transformer based on large margin learning classifier, Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 2886-2891.(EI)
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    Xizhao Wang(*), Feng Yang, Yan Li, A discussion on the overlapping in fuzzy production rule reasoning, Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 4557-4562.(EI)
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    Xizhao Wang(*), Xuguang Wang and Jun Shen, The representation of interaction among fuzzy rules, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3098-3103.(EI)
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    Xizhao Wang(*), Jun Shen and Xuguang Wang, Using 2-additive fuzzy measure to represent the interaction among if-then rules, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 2797-2801.(EI)
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    Xizhao Wang(*), Yan Ha and Degang Chen, On the reduction of fuzzy rough sets, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3174-3178.(EI)
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    Xizhao Wang(*), Sufang Zhang and Junhai Zhai, A nonlinear integral defined on partition of set and its fundamental properties, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3092-3097.(EI)
  • [32]
    Xizhao Wang(*),Hui Zhang, An upper bound of input perturbation for RBFNNs sensitivity analysis, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 4704-4708.(EI)
  • [31]
    Xizhao Wang(*), Ying Xu, Multilevel weighted fuzzy reasoning with interaction, Proceedings of 2005 IEEE International Conference on Systems,Man and Cybernetics, Waikoloa, Hawaii, USA, 10-12 October 2005, Proceedings pp: 708-715.(EI)
  • [30]
    Xizhao Wang(*), Chunguo Li, A new definition of sensitivity for RBFNN and its applications to feature reduction, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 81-86.(EI)
  • [29]
    Juan Sun(*), Xizhao Wang, An initial comparison on noise resisting between crisp and fuzzy decision trees, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 2545-2550.(EI)
  • [28]
    John W.T. Lee(*), Xizhao Wang, Jinfeng Wang, Finding reducts for ordinal decision tables, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3143-3147.(EI)
  • [27]
    Xizhao Wang(*), Chunru Dong, Daniel Yeung, A study on generalization capability of weighted fuzzy production rules with maximum entropy, Proceedings of 2004 IEEE International conference on systems, Man and cybernetics, Hague, Holland, 10-13 October, 2004, Proceedings pp: 3181-3186.(EI)
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    Xizhao Wang(*), Xiaojun Wang, A new methodology for determining fuzzy densities in the fusion model based on fuzzy integral, Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29, August, 2004, Proceedings pp: 2028-2031.(EI)
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    Xizhao Wang(*), Xiaoying Lu, Feng Zhang, Feature selection based on fuzzy extension matrix for multi-class problem. Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29, August, 2004, Proceedings pp: 2032-2035.(EI)
  • [24]
    Xizhao Wang(*), Junfen Chen, Multiple neural networks fusion model based on choquet fuzzy integral, Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August, 2004, Proceedings pp: 2024-2027.(EI)
  • [23]
    Xizhao Wang(*), Huimin Feng, Nonnegative set functions in multiple classifier fusion, Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August, 2004, Proceedings pp: 2020-2023.(EI)
  • [22]
    Wing Ng(*), Daniel Yeung, Xizhao Wang, Ian Cloete, A study of the difference between partial derivative and stochastic neural network sensitivity analysis, Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August, 2004, Proceedings pp: 4283-4288.(EI)
  • [21]
    Yong Li(*), Xizhao Wang, Qiang Hua, Using bp-network to construct fuzzy decision tree, Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1791-1795.(EI)
  • [20]
    Yan Li(*), Xizhao Wang, Minghu Ha, On-line multi-cbr agent dispatching, Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 2071-2075.(EI)
  • [19]
    Suyun Zhao(*), Xizhao Wang, A fuzzy model of rough sets, Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1687-1691.(EI)
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    Dazhong Liu(*), Xizhao Wang, J. W. T. Lee, Ordinal fuzzy sets and rough sets, Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi’an,China, 2-5 November 2003, Proceedings pp: 1438-1441.(EI)
  • [17]
    Qiang He(*), Xizhao Wang, Hongjie Xing, A fuzzy classification method based on support vector machine, Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003,Proceedings pp: 1237-1240.(EI)
  • [16]
    Qunfeng Zhang(*), Xizhao Wang, Jinghong Wang, A further study on simplification of decision tables, Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003,Proceedings pp: 1657-1661.(EI)
  • [15]
    Hua Li(*), Xizhao Wang, Yong Li, Using mutual information for selecting continuous-valued, Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1496-1499.(EI)
  • [14]
    Shixin Zhao(*), Xizhao Wang, Core and reduction from mutual relation view and their fuzzy generalization, 2003 IEEE International Conference on Systems, Man & Cybernetics, Washington DC, USA, 6-9 October 2003, Proceedings pp: 2611-2616.(EI)
  • [13]
    Yan Li(*) , Minghu Ha, Xizhao Wang, Principle and Design of Fuzzy Controller Based on Fuzzy Learning from Examples, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1441-1446.(EI)
  • [12]
    Dongmei Huang(*), Xizhao Wang, Minghu Ha, The Optimization Problem of the Fuzzy Bi-Branches Decision Trees, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1667-1668.(EI)
  • [11]
    Dazhong Liu(*), Xizhao Wang, John W.T. Lee, Correlation Based Generating Rules for Fuzzy Classification,Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1733-1736.(EI)
  • [10]
    Hongjie Xing(*), Xizhao Wang, Qiang He, Hongwei Yang, The Multistage Support Vector Machine, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1815-1818.(EI)
  • [9]
    Xizhao Wang(*), Minghua Zhao, Daniel So Yeung, Parametric Sensitivity in Building Fuzzy Decision Trees: an Experimental Analysis, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1819-1823.(EI)
  • [8]
    Xizhao Wang(*), Hongwei Yang, Minghua Zhao, Juan Sun, A Decision Tree Based on Hierarchical Decomposition, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1824-1828.(EI)
  • [7]
    Lijuan Wang(*), Xizhao Wang, Minghu Ha, Yinshan Gu, Mining the Weights of Similarity Measure Through Learning, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1837-1841.(EI)
  • [6]
    Daniel So Yeung(*), Juan Sun, Xizhao Wang, An Initial Comparison of Generalization-Capability between Crisp and Fuzzy Decision Trees, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1846-1851.(EI)
  • [5]
    Shenshan Qiu(*), Eric C.C. Tsang, Daniel S. Yeung, Xizhao Wang, Energy Function Criterion for Discrete Hopfield-Type Neural Network with Delay, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 2240-2244.(EI)
  • [4]
    Ruifeng Xu(*), D. S. Yeung, Xizhao Wang, Using neural network classifier in post-processing system for handwritten Chinese character recognition, IEEE International Conference on Systems, Man, and Cybernetics, TUCSON, AZ, USA, 07-10 October 2001, Proceedings pp: 1497-1502.(EI)
  • [3]
    E. C. C. Tsang(*), D. S. Yeung, Xizhao Wang, Learning weights of fuzzy production rules by a max-min neural network, IEEE International Conference on Systems, Man, and Cybernetics, TUCSON, AZ, USA, 07-10 October 2001,Proceedings pp: 1485-1490.(EI)
  • [2]
    Xizhao Wang(*), D. S. Yeung, Using fuzzy integral to modeling case-based reasoning with feature interaction, in Proceedings of IEEE International Conference on Systems, Man, and Cybernetics,Nashville, Tennessee, USA, 8-11 October 2000, pp: 3660-3665.(EI)
  • [1]
    D. S. Yeung(*), Xizhao Wang, Using a neuro-fuzzy technique to improve the clustering based on similarity, in Proceedings of IEEE International Conference on IEEE International Conference on Systems, Man, and Cybernetics, Nashville, Tennessee, USA, 8-11 October 2000, Proceedings pp: 3693-3698.(EI)

Recruitment

JMLC papers

Reference

Group Meeting