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New: DMKD Special Issue on Data Mining with Matrices, Graphs and Tensors

 

Postoctoral Research Associate                                                                                        

School of Computing & Information Sciences

Florida International University

ECS 251, Miami, FL 33199

 

Phone: 305-348-1218

Email: feiwang at cs.fiu.edu

 

Research Interests: Machine Learning and Data Mining

Honors and Awards

  • Postdoctoral Travel Grant, 21st International Joint Conference on Artificial Intelligence, 2009
  • Postdoctoral Travel Grant, 9th SIAM International Conference on Data Mining, 2009
  • First Class Excellent Doctoral Thesis, Tsinghua University, 2008
  • Student Travel Grant, 23rd International Conference on Machine Learning, 2006
  • Student Travel Grant, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006
  • Student Travel Grant, 7th SIAM International Conference on Data Mining, 2007
  • Excellent Graduate Student, Tsinghua University, 2007
  • New Academic Star Honorable Mention, Tsinghua University, 2007
  • New Academic Star, Department of Automation, Tsinghua University, 2007, 2008
  • China Ship System Scholarship, Tsinghua University, 2007
  • Excellent oral presentation award, doctoral forum, Department of Automation, Tsinghua University, 2006, 2007
  • Schneider Scholarship, Tsinghua University , 2006
  • Excellent Undergraduate Student, Shaanxi Province
  • Excellent Undergraduate Student, Xidian University

Presentations

     Conference Tutorials

  • "Data Mining with Graphs and Matrices", To be presented, Sparks, Nevada, SDM 2009
  • "Information and Knowledge Management with Graphs and Matrices", Napa Valley, California, CIKM 2008

     Invited Talks

  • "Graph Based Semi-supervised Learning", Department of Computer Science and Engineering, University of Texas at Arlington, 2009
  • "Graph Based Semi-supervised Learning", Department of Computer Science, University of Miami, 2008
  • "Graph Based Semi-supervised Learning", School of Computing and Information Sciences, Florida International University, 2008
  • "Graph Based Semi-supervised Learning", Department of Computer Science, Beijing Jiaotong University, 2008

     Conference Presentations

  • "Preference Learning with Extreme Examples", Pasadena, California, IJCAI 2009
  • "Generalized Cluster Aggregation", Pasadena, California, IJCAI 2009
  • "Semi-supervised Regression for Evaluating Convenience Store Location", Pasadena, California, IJCAI 2009
  • "Straightforward Feature Selection for Scalable Latent Semantic Indexing", Reno, Nevada, SDM 2009
  • "Local Relevance Weighted Maximum Margin Criterion for Text Classification", Reno, Nevada, SDM 2009
  • "Semi-supervised Clustering via Matrix Factorizations", Atlanta, Georgia, SDM 2008
  • "Weighted Consensus Clustering", Atlanta, Georgia, SDM 2008
  • "Fast Multilevel Transduction on Graphs", Minneapolis, Minnesota, SDM 2007
  • "Optimal Dimensionality Discriminant Analysis and Its Application to Image Segmentation", Minneapolis, Minnesota,  CVPR 2007 Workshop on Component Analysis Methods in Classification, Clustering, Modeling and Estimation Problems in Computer Vision
  • "Label Propagation Through Linear Neighborhoods", Pittsburgh, Pennsylvania, ICML 2006

     Poster Presentations

  • "Beyond the Graphs: Semi-parametric Semi-supervised Discriminant Analysis", Miami, Florida, CVPR 2009
  • "Semi-supervised Metric Learning by Maximizing the Constraint Margin", Napa Valley, California, CIKM 2008
  • "Semi-supervised Ranking Aggregation", Napa Valley, California, CIKM 2008
  • "Semi-supervised Dimensionality Reduction", Minnesota, Minneapolis, SDM 2007
  • "Feature Extraction by Maximizing the Average Neighborhood Margin", Minneapolis, Minnesota, CVPR 2007
  • "Semi-supervised Classification by Linear Neighborhood Propagation", New York, New York, CVPR 2006
  • "A Discriminative Method For Semi-Automated Tumorous Tissues Segmentation of MR Brain Images ", New York, New York, CVPR Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA). 2006.

Professional Activities

      Journal Refrees

  • Guest Editor, Journal of Data Mining and Knowledge Discovery Special Issue on Data Mining with Matrices, Graphs and Tensors, 2009
  • Reviewer, ACM Transactions on Sensor Networks, 2008, 2009
  • Reviewer, IEEE Transactions on Signal Processing, 2008
  • Reviewer, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 2009
  • Reviewer, IEEE Transactions on Knowledge and Data Engineering, 2008, 2009
  • Reviewer, IEEE Transactions on Neural Networks, 2007, 2008, 2009 
  • Reviewer, Journal of Machine Learning Research, 2009 
  • Reviewer, Artificial Intelligence, 2009 
  • Reviewer, Data Mining and Knowledge Discovery, 2009 
  • Reviewer, Statistical Analysis and Data Mining, 2009 
  • Reviewer, Pattern Recognition, 2008, 2009 
  • Reviewer, Information Processing & Management, 2007,2008 
  • Reviewer, Neurocomputing, 2007, 2008, 2009 
  • Reviewer, International Journal of Pattern Recognition and Artificial Intelligence, 2009 

      Conference Committee

  • Program Committee Member, 1st Asian Conference on Machine Learning (ACML09)
  • Program Committee Co-Chair, ICDM 2009 Workshop on Optimization Based Techniques for Emerging Data Mining Problems (OEDM09)
  • Program Committee Member, KDD 2009 Workshop on Data Mining using Matrices and Tensors (DMMT09)
  • Local Arrangement Co-Chair, 2009 International Conference on Machine Learning and Applications (ICMLA09)
  • Program Committee Member, 9th International Conference on Data Mining (ICDM09)
  • International Program Committee Member, The 6th International Conference on Informatics in Control, Automation and Robotics (ICINCO09)
  • Program Committee Member, KDD 2008 Workshop on Data Mining using Matrices and Tensors (DMMT08)
  • Program Committee Member, ICMLA 2007, 2008
  • Technical Committee Member, WCCI 2008

      Conference Reviewer

  • Reviewer, The 14th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2008
  • Reviewer, The 31st Annual International ACM SIGIR Conference 2008
  • Reviewer, The 8th SIAM International Conference on Data Mining 2008
  • Reviewer, The 2007 IEEE/WIC/ACM International Conference on Web Intelligence 2007
  • Reviewer, IEEE International Joint Conference on Neural Networks 2006
  • Reviewer, IEEE International Joint Conference on Neural Networks 2007

Publications

     Book Chapter

  1. Liang Xiong, Fei Wang, Changshui Zhang. Guide Manifold Alignment by Relative Comparisons. Invited Chapter in Encyclopedia of Data Warehousing and Mining - 2nd Edition. 2008.

Journal Paper

  1. Bin Zhao,Fei Wang, Changshui Zhang. Block Quantized Support Vector Ordinal Regression. IEEE Transactions on Neural Networks (TNN). Vol.20, no.5. 882-890. 2009.
  2. Fei Wang, Changshui Zhang, Tao Li. Clustering with Local and Global Regularizations. IEEE Transactions on Knowledge and Data Engineering (TKDE). To Appear. 2009.
  3. Peng Cui, Lifeng Sun, Fei Wang, Shiqiang Yang. Contextual Mixture Tracking. IEEE Transactions on Multimedia (TMM). Vol. 11, no.2, 333-341. 2009.
  4. Jingdong Wang, Fei Wang, Changshui Zhang, Helen C. Shen, Long Quan. Linear Neighborhood Propagation and Its Applications. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Vol. 31, No. 9, Page 1600-1615, September 2009.
  5. Fei Wang, Changshui Zhang. Semi-supervised Learning Based on Generalized Point Charge Models. IEEE Transactions on Neural Networks (TNN). vol. 19, no. 7, 1309-1311. 2008.
  6. Fei Wang, Changshui Zhang. Label Propagation Through Linear Neighborhoods. IEEE Transactions on Knowledge and Data Engineering (TKDE). vol.20, no.1, 55-67. 2008.
  7. Gang Chen, Fei Wang, Changshui Zhang. Collaborative Filtering Using Orthogonal Nonnegative Matrix Tri-factorization. Information Processing & Management. To Appear. 2009.
  8. Dan Zhang, Fei Wang, Zhenwei Shi, Changshui Zhang. Interactive Localized Content-Based Image Retrieval Using Multiple Instance Active Learning. Pattern Recognition. To Appear. 2009.
  9. Fei Wang, Xin Wang, Daoqiang Zhang, Changshui Zhang, Tao Li. marginFace: A Novel Face Recognition Method by Average Neighborhood Margin Maximization. Pattern Recognition. To Appear. 2009.
  10. Fei Wang, Jingdong Wang, Changshui Zhang, James T. Kwok. Face Recognition Using Spectral Features. Pattern Recognition. vol. 40, no. 10, pages 2786-2797, October, 2007.
  11. Fei Wang, Changshui Zhang. Robust Self-Tuning Semi-Supervised Learning. Neurocomputing. vol. 70, 2931-2939. 2007.
  12. Fei Wang, Xin Wang. Neighborhood Discriminative Tensor Mapping. Neurocomputing. vol. 72, no. 7-9. 2035-2039. 2009.
  13. Yangqiu Song, Changshui Zhang, Jianguo Lee, Fei Wang, Shiming Xiang, Dan Zhang. Semi-Supervised Discriminative Classification with Application to Tumorous Tissues Segmentation of MR Brain Images. Pattern Analysis & Applications. Vol. 12, no.2, 99-115. 2009.

Conference Paper

  1. Fei Wang, Xin Wang, Bo Shao, Tao Li, Mitsunori Ogihara. Tag Integrated Multi-label Music Style Classification with Hypergraphs. The 10th International Society for Music Information Retrieval Conference (ISMIR). Kobe, Japan, October 26-30. To Appear. 2009. (Oral Presentation)
  2. Fei Wang, Xin Wang and Tao Li. Generalized Cluster Aggregation. The 21st International Joint Conference on Artificial Intelligence (IJCAI) Pasadena, California, July 11-17. To Appear. 2009. (Oral Presentation)
  3. Dan Zhang, Fei Wang, Luo Si, Tao Li. Maximum Margin Multiple Instance Clustering. The 21st International Joint Conference on Artificial Intelligence (IJCAI) Pasadena, California, USA, July 11-17. To Appear. 2009. (Oral Presentation)
  4. Fei Wang, Bin Zhang, Ta-Hsin Li, Wen jun Yin, Jin Dong, Tao Li. Preference Learning with Extreme Examples. The 21st International Joint Conference on Artificial Intelligence (IJCAI). Pasadena, California, USA, July 11-17. To Appear. 2009. (Oral Presentation)
  5. Fei Wang, Xin Wang and Tao Li. Beyond the Graphs: Semi-Parametric Semi-Supervised Discriminant Analysis. IEEE Comp. Society Conf. on Computer Vision and Pattern Recognition (CVPR), Miami, Florida, USA, June 20-25. To Appear. 2009.
  6. Bin Zhao, James Kwok,Fei Wang, and Changshui Zhang. Unsupervised Maximum Margin Feature Selection with Manifold Regularization. IEEE Comp. Society Conf. on Computer Vision and Pattern Recognition (CVPR), Miami, Florida, USA, June 20-25. To Appear. 2009.
  7. Gang Chen, Jianwen Zhang, Fei Wang, and Changshui Zhang. Efficient Multi-Label Learning with Hypergraph Regularization. IEEE Comp. Society Conf. on Computer Vision and Pattern Recognition (CVPR), Miami, Florida, USA, June 20-25. To Appear. 2009.
  8. Fei Wang, Chris Ding, Tao Li. Integrated KL (K-means -- Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations. The 9th SIAM Conference on Data Mining (SDM). John Ascuaga's Nugget. Sparks. Nevada. To Appear. 2009. (Oral Presentation)
  9. Peng Cui, Fei Wang, Li-Feng Sun, Shi-Qiang Yang. A Joint Matrix Factorization Approach to Unsupervised Action Categorization. The 8th IEEE International Conference on Data Mining (ICDM). Pisa, Italy. 15-19, Dec. 2008. To Appear.
  10. Bin Zhao, Fei Wang, Changshui Zhang. Maximum Margin Embedding. The 8th IEEE International Conference on Data Mining (ICDM). 1127-1132. Pisa, Italy. 15-19, Dec. 2008.
  11. Fei Wang, Shouchun Chen, Tao Li, Changshui Zhang. Semi-Supervised Metric Learning by Maximizing Constraint Margin. ACM 17th Conference on Information and Knowledge Management (CIKM). 1457-1458. Napa Valley, California, USA. 2008.
  12. Shouchun Chen, Fei Wang, Yangqiu Song, Changshui Zhang. Semi-supervised Ranking Aggregation. ACM 17th Conference on Information and Knowledge Management (CIKM). 1427-1428. Napa Valley, California, USA. 2008.
  13. Bin Zhao, Fei Wang, Changshui Zhang. CutS3VM: A Fast Semi-Supervised SVM Algorithm. The 14th ACM SIGKDD Int'l Conf. on Knowledge Discovery & Data Mining (KDD).  Las Vegas, Nevada, USA. To Appear. 2008. (Long Presentation)
  14. Dan Zhang, Fei Wang, Zhenwei Shi, Changshui Zhang. Localized Content-Based Image Retrieval Using Multiple Instance Active Learning. The 15th IEEE International Conference on Image Processing (ICIP). To Appear. 2008.
  15. Bin Zhao, Fei Wang, Changshui Zhang. Efficient Multi-Class Maximum Margin Clustering. The 25th International Conference on Machine Learning (ICML). Helsinki, Finland. To Appear. 2008. (Oral Presentation)
  16. Fei Wang, Changshui Zhang. On Discriminative Semi-supervised Classification. The 23rd AAAI Conference on Artificial Intelligence (AAAI). July 13-17, Chicago, Illinois, USA. 2008. (Oral Presentation)
  17. Fei Wang, Tao Li, Gang Wang, Changshui Zhang. Semi-supervised Classification Using Local and Global Regularization. The 23rd AAAI Conference on Artificial Intelligence (AAAI). July 13-17, Chicago, Illinois, USA. 2008. (Oral Presentation)
  18. Dan Zhang, Fei Wang, Changshui Zhang, Tao Li. Multi-view Local Learning. The 23rd AAAI Conference on Artificial Intelligence (AAAI). July 13-17, Chicago, Illinois, USA. 2008. (Oral Presentation)
  19. Bin Zhang, Fei Wang, Ta-Hsin Li, Wen jun Yin, Jin Dong. Classification by Discriminative Regularization. The 23rd AAAI Conference on Artificial Intelligence (AAAI). July 13-17, Chicago, Illinois, USA. 2008. (Oral Presentation).
  20. Bin Zhao, Fei Wang, Changshui Zhang. Efficient Maximum Margin Clustering Via the Cutting Plane Algorithm. The 8th SIAM Conference on Data Mining (SDM). Hyatt Regency Hotel, Atlanta, Georgia. To Appear. 2008. (Oral Presentation)
  21. Fei Wang, Tao Li, Changshui Zhang. Semi-Supervised Clustering via Matrix Factorization. The 8th SIAM Conference on Data Mining (SDM). Hyatt Regency Hotel, Atlanta, Georgia. To Appear. 2008. (Oral Presentation)
  22. Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang. Semi-supervised Multi-label Learning by Solving a Sylvester Equation. The 8th SIAM Conference on Data Mining (SDM). Hyatt Regency Hotel, Atlanta, Georgia. To Appear. 2008.
  23. Dan Zhang, Jingdong Wang, Fei Wang, Changshui Zhang. Semi-Supervised Classification with Universum. The 8th SIAM Conference on Data Mining (SDM). Hyatt Regency Hotel, Atlanta, Georgia. To Appear. 2008.
  24. Bin Zhao, Fei Wang, Changshui Zhang, Yangqiu Song. Active Model Selection for Graph Based Semi-Supervised Learning. The 33rd Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP). Las Vegas, Nevada. To Appear. 2008. (Oral Presentation)
  25. Fei Wang, Xin Wang, Tao Li. Efficient Label Propagation for Interactive Image Segmentation. The 6th Int'l Conf. on Machine Learning and Applications (ICMLA). Cincinnati, Ohio, December 13-15, 2007. (Oral Presentation)
  26. Fei Wang, Tao Li. Gene Selection via Matrix Factorization. The 7th IEEE International Symposium on Bioinformatics & Bioengineering (BIBE). pp. 1046-1050. Harvard Medical School Conference Center, Cambridge-Boston, Massachusetts, USA. 2007.
  27. Shouchun Chen, Fei Wang, Changshui Zhang. Simultaneous Heterogeneous Data Clustering Based on Higher Order Relationships. Proceedings of the Workshop on Mining Graphs and Complex Structures (MGCS07), in conjuction with the 7th IEEE International Conference on Data Mining (ICDM). pp. 387-392. Omaha, USA. 2007. (Oral Presentationn)
  28. Gang Chen, Fei Wang, Changshui Zhang. Collaborative Filtering Using Orthogonal Nonnegative Matrix Tri-factorization. Proceedings of the Workshop on High Performance Data Mining, in conjuction with the 7th IEEE International Conference on Data Mining (ICDM). pp. 303-308. Omaha, USA. 2007. (Oral Presentation)
  29. Liang Xiong, Fei Wang, Changshui Zhang. Multilevel Belief Propagation for Fast Inference on Markov Random Fields. The 7th IEEE International Conference on Data Mining (ICDM). Omaha, USA. To Appear. 2007. (Oral Presentationn)
  30. Liang Xiong, Fei Wang, Changshui Zhang. Semi-Definite Manifold Alignment. The 18th European Conference on Machine Learning (ECML). pp. 773-781, Warsaw, Poland. 2007.
  31. Fei Wang, Changshui Zhang, Tao Li. Regularized Clustering for Documents. The 30th Int'l ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR). pp. 95-102, Amsterdam. 2007. (Oral Presentation)
  32. Fei Wang, Changshui Zhang, Tao Li. Clustering with Local and Global Regularization. The 22nd National Conference on Artificial Intelligence (AAAI). pp. 657-662, Vancouver, Canada. 2007. (Oral Presentation)
  33. Fei Wang, Changshui Zhang. Feature Extraction by Maximizing the Average Neighborhood Margin. IEEE Comp. Society Conf. on Computer Vision and Pattern Recognition (CVPR). pp. 1-8, Minneapolis, Minnesota, 2007.
  34. Fei Wang, Changshui Zhang. Fast Multilevel Transduction on Graphs. The 7th SIAM Conference on Data Mining (SDM). Radisson University Hotel, Minneapolis, Minnesota. To Appear. 2007. (Oral Presentation)
  35. Fei Wang, Shijun Wang, Changshui Zhang, Ole Winther. Semi-Supervised Mean Fields. The 11th Int'l Conf. on Artificial Intelligence and Statistics (AISTATS). JMLR Workshop and Conference Proceedings Volume 2: AISTATS 2007, pages: 596-603. San Juan, Puerto Rico. 2007.
  36. Bin Zhao, Fei Wang, Changshui Zhang. Smoothness Maximization via Gradient Descents. The 32nd Int'l Conf. on Acoustics, Speech, and Signal Processing (ICASSP). vol. 2, 609-612. Honolulu, Hawaii. 2007.
  37. Fei Wang, Sheng Ma, Liuzhong Yang, Tao Li. Recommendation on Item Graphs. The 6th IEEE International Conference on Data Mining (ICDM). Hongkong, China. 1119-1123. 18-22, Dec. 2006.
  38. Fei Wang, Jingdong Wang, Changshui Zhang and Helen C. Shen. Semi-Supervised Classification Using Linear Neighborhood Propagation. IEEE Comp. Society Conf. on Computer Vision and Pattern Recognition (CVPR) vol. 1, pp.160-167. New York University, New York, New York, USA, June 17-22, 2006.
  39. Yangqiu Song, Changshui Zhang, Jianguo Lee, Fei Wang. A Discriminative Method For Semi-Automated Tumorous Tissues Segmentation of MR Brain Images. The 2006 IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) at the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). pp.79, New York University, New York, New York, USA, June 17-22, 2006. 
  40. Fei Wang, Changshui Zhang. Label Propagation Through Linear Neighborhoods. The 23rd International Conference on Machine Learning (ICML). 985-992. Carnegie Mellon University, Pittsburgh, Pennsylvania, USA, June 25-29, 2006. (Oral Presentation)
  41. Fei Wang, Changshui Zhang and Naijiang Lu. Boosting GMM and Its Two Applications. In: Nikunj C. Oza, Robi Polikar, Josef Kittler and Fabio Roli (Eds.), Lecture Notes in Computer Science, Proceedings, Springer-Verlag GmbH, ISBN 3-540-26306-3, vol. 3541 / 2005: pp. 12. Sixth International Workshop Multiple Classifier Systems (MCS). Seaside, California, June 13-15, 2005.
  42. Fei Wang, Jingdong Wang and Changshui Zhang. Spectral Feature Analysis. The 2005 IEEE International Joint Conference on Neural Networks (IJCNN). Volume 3, pp. 1971 - 1976. Montreal, Canada, July 31-August 4, 2005.
  43. Fei Wang, Changshui Zhang. Spectral Clustering for Time Series. In: Lecture Notes in Computer Science, Proceedings, Part I, Springer-Verlag GmbH, ISBN 3-540-28757-4, vol. 3686/2005: pp. 345. The 3rd International Conference on Advances in Pattern Recognition and Data Mining (ICAPR). Bath, UK, August 22-25, 2005.