Conferences: ICDM(14), CIKM(8), AAAI(6), IJCAI(6), KDD(4), ICDE(4), MM(2), ICML(1), CVPR(1)
Journals: KAIS(6), TKDE(4), TSMC(4), DSS(3), MMS(3), DMKD(2), TMM(2), TPAMI(1), TOIS(1)

2013 and Beyond

  1. Hanning Yuan, Meng Fang, and Xingquan Zhu, Hierarchical Sampling for Multi-Instance Ensemble Learning, IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2012.245, 2013.
  2. Yifan Fu, Xingquan Zhu, and Ahmed Elmagarmid, Active Learning with Optimal Instance Subset Selection, IEEE Transactions on Cybernetics, 43(2):464-475, April 2013.
  3. Xindong Wu, Kui Yu, Wei Ding, Hao Wang, and Xingquan Zhu, Online Feature Selection with Streaming Features, IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(5):1178-1192, May 2013.
  4. Bin Li, Ling Chen, Xingquan Zhu, and Chengqi Zhang, Noisy but Non-Malicious User Detection in Social Recommender Systems, World Wide Web Journal, accepted on March 28 2012, DOI: 10.1007/s11280-012-0161-9
  5. Yifan Fu, Xingquan Zhu, and Bin Li, A Survey on Instance Selection for Active Learning, Knowledge and Information Systems, 35(2):249-283, May 2013.
  6. Meng Fang, Jie Yin, Xingquan Zhu, and Chengqi Zhang, Active Class Discovery and Learning for Networked Data, Proceedings of the 13th SIAM International Conference on Data Mining (SDM '13), May 2-4, 2013, Austin, Texas, USA.
  7. Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Graph Stream Classification using Labelled and Unlabeled Graphs, Proceedings of the 29th IEEE International Conference on Data Engineering (ICDE '13), April 8-11, 2013, Brisbane, Australia.
  8. Lianhua Chi, Bin Li, and Xingquan Zhu, Fast Graph Stream Classification Using Discriminative Clique Hashing, Proc. Of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2013), April 14-17, Brisbane, Australia. (Best Paper Award)

2012

  1. Patent: Relational Pattern Discovery Across Multiple Databases, Xindong Wu and Xingquan Zhu, United States Patent, No.8112440, Filled: April 14, 2008, Granted: February 7, 2012.
  2. Xingquan Zhu, Editorial: Special Issue on Data Mining Applications and Case Study, Neurocomputing, 92:1-2, 2012.
  3. Zhenfeng Zhu, Xingquan Zhu, Yuefei Guo, Yangdong Ye, and Xiangyang Xue, Inverse Matrix-free Incremental Proximal Support Vector Machine, Decision Support Systems, 53(3):395-405, June 2012.
  4. Meng Fang, Xingquan Zhu, Bin Li, Wei Ding, and Xindong Wu, Self-Taught Active Learning from Crowds, Proceedings of the 12th IEEE International Conference on Data Mining (ICDM '12), December 10-13, 2012, Brussels, Belgium.
  5. Bin Li, Xingquan Zhu, Lianhua Chi, and Chengqi Zhang, Nested Subtree Hash Kernels for Large-scale Graph Classification over Streams, Proceedings of the 12th IEEE International Conference on Data Mining (ICDM '12), December 10-13, 2012, Brussels, Belgium.
  6. Meng Fang and Xingquan Zhu, I Don't Know the Label: Active Learning with Blind Knowledge, Proceedings of the 21st International Conference on Pattern Recognition (ICPR '12), November 11-15, 2012, Tsukuba, Japan. (Best Student Paper Award)
  7. Shirui Pan, Xingquan Zhu, and Mmeng Fang, Top-k Correlated Subgraph Query for Data Streams, Proc. Of the 21st International Conference on Pattern Recognition (ICPR-12), November 11-15, 2012, Tsukuba, Japan.
  8. Shirui Pan and Xingquan Zhu, CGStream: Continuous Correlated Graph Query for Data Streams, Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM '12), Oct. 29 - Nov. 2, 2012, Hawaii, USA.
  9. Guodong Song, Ling Chen, Xingquan Zhu, and Chengqi Zhang, TCSST: Transfer Classification of Short & Sparse Text Using External Data, Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM '12), Oct. 29 - Nov. 2, 2012, Hawaii, USA.
  10. Shirui Pan and Xingquan Zhu, Continuous Top-k Query for Graph Streams, Proc. Of The 21st ACM Conference on Information and Knowledge Management (CIKM-12), Oct. 29 – Nov. 2, 2012, Hawaii, USA.
  11. Zhenfeng Zhu, Xingquan Zhu, Yuefei Guo, Yangdong Ye, and Xiangyang Xue, Parallel Proximal Support Vector Machine for High-dimensional Pattern Classification, Proc. Of The 21st ACM Conference on Information and Knowledge Management (CIKM-12), Oct. 29 – Nov. 2, 2012, Hawaii, USA.
  12. Meng Fang, Xingquan Zhu, and Chengqi Zhang, Active Learning from Oracle with Knowledge Blind Spot, Proc. of the 26th Annual American Association for the Advancement of Artificial Intelligence Conference (AAAI-12) [Poster], July 22-26, 2012, Toronto, Canada.

2011

  1. Xingquan Zhu, Cross Domain Semi-Supervised Learning Using Feature Formulation, IEEE Transactions on Systems Man and Cybernetics, Part B, 41(6):1727-1638, 2011.
  2. Xingquan Zhu, Bin Li, Xindong Wu, Dan He, and Chengqi Zhang, CLAP: Collaborative Pattern Mining for Distributed Information Systems. Decision Support Systems, 52(1):40-51, 2011.
  3. Dan He, Xingquan Zhu, and Xindong Wu, Mining Approximate Repeating Patterns from Sequence Data with Gap Constraints, Computational Intelligence, 27(3):336-362, 2011.
  4. Xingquan Zhu, Wei Ding, Philip S. Yu, and Chengqi Zhang, One-Class Learning and Concept Summarization for Data Streams, Knowledge and Information Systems, special issue on Data Warehousing and Knowledge Discovery from Sensors and Streams (invited submission), 28(3):523-553, 2011.
  5. Yan Zhang, Xingquan Zhu, Xindong Wu, and Jeffrey P. Bond, Corrective Classification: Learning from Data Imperfections with Aggressive and Diverse Ensembling, Information Systems, 36(8):1135-1157, December 2011
  6. Ddonghong Sun, Li Liu, Peng Zhang, Xingquan Zhu, and Yong Shi, Decision Rule Extraction for Regularized Multiple Criteria Linear Programming Model. International Journal of Data Warehousing and Mining, 7(3): 88-101, 2011.
  7. Peng Zhang, Xingquan Zhu, Yong Shi, Li Guo, and Xindong Wu, Robust Ensemble Learning for Mining Noisy Data Streams, Decision Support Systems, 50(2):469-479, 2011.
  8. Book Chapter: M. Slavik, X. Zhu, I. Mahgoub, T. Khoshgoftaar, and R. Narayanan, Data Intensive Computing: A Biomedical Case Study in Gene Selection and Filtering, in Handbook of Data Intensive Computing, edited by Borko Furht and Armando Escalante, Springer, 2011.
  9. Dan He, Xingquan Zhu, and D. Stott Parker, How Does Research Evolve? Pattern Mining for Research Meme Cycles, Proceedings of the 11th IEEE International Conference on Data Mining (ICDM '11), Dec. 11-14, 2011, Vancouver, Canada.
  10. Peng Zhang, Byron J. Gao, Xingquan Zhu, and Li Guo, Enabling Fast Lazy Learning for Data Streams, Proceedings of the 11th IEEE International Conference on Data Mining (ICDM '11), Dec. 11-14, 2011, Vancouver, Canada.
  11. Peng Zhang, Jun Li, Peng Wang, Byron J. Gao, Xingquan Zhu, and J. Gao, Enabling Efficient Prediction for Ensemble Models on Data Streams, Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '11), San Diego, CA, USA, August 21-24, 2011.
  12. Zhenfeng Zhu, Xingquan Zhu, Yangdong Ye, Yuefei Guo, and Xiangyang Xue, Transfer Active Learning, in Proc. Of the 20th ACM Conference on Information and Knowledge Management (CIKM-11), Glasgow, UK, Oct. 24-28, 2011.
  13. Yifan Fu, Bin Li, and Xingquan Zhu, Do They Belong to the Same Class? Active Learning by Querying Pairwise Label Homogeneity, in Proc. Of the 20th ACM Conference on Information and Knowledge Management (CIKM-11), Glasgow, UK, Oct. 24-28, 2011.
  14. Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, and Xingquan Zhu, Tracking User-Preference Varying Speed in Collaborative Filtering, Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI '11), San Francisco, USA, August 7-11, 2011.
  15. Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, and Xindong Wu, Cross Domain Collaborative Filtering over Time, Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI '11), Barcelona, Spain, July 16-22, 2011.
  16. Guohua Liang, Xingquan Zhu, and Chengqi Zhang, An Empirical Study of Bagging Predictors for Different Learning Algorithms, Proc. of the 25th Annual American Association for the Advancement of Artificial Intelligence Conference (AAAI-11) [Poster], August 7-11, San Francisco, USA, 2011.
  17. Yifan Fu and Xingquan Zhu, Optimal Subset Selection for Active Learning, Proc. of the 25th Annual American Association for the Advancement of Artificial Intelligence Conference (AAAI-11) [Poster], August 7-11, San Francisco, USA, 2011.
  18. Ting Guo, Zhanshan Li, Ruizhi Guo, and Xingquan Zhu, Large Scale Diagnosis using Associations between System Outputs and Components, Proc. of the 25th Annual American Association for the Advancement of Artificial Intelligence Conference (AAAI-11) [Poster], August 7-11, San Francisco, USA, 2011.
  19. Hui Wu, Guangzhi Qu, and Xingquan Zhu, Self-Adjust Local Connectivity Analysis for Spectral Clustering, Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-11), Shenzhen, China, May 24-27, 2011.

2010

  1. Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, Active Learning from Stream Data Using Optimal Weight Classifier Ensemble, IEEE Transactions on Systems Man and Cybernetics, Part B, 40(6):1607-1621, December 2010.
  2. Zhenfeng Zhu, Yuefei Guo, Xingquan Zhu, and Xiangyang Xue, Normalized Dimensionality Reduction Using Nonnegative Matrix Factorization, Neurocomputing, 73(10-12):1783-1793, 2010,
  3. Abu Kamal, Xingquan Zhu, Abhijit Pandya, Sam Hsu, and R. Narayanan, Feature Selection for Datasets with Imbalanced Class Distributions, International Journal of Software Engineering and Knowledge Engineering, 20(2):113-137, 2010.
  4. Peng Zhang, Xingquan Zhu, and Yong Shi, Multiple Criteria Programming Models for VIP E-Mail Behavior Analysis, Web Intelligence and Agent Systems, 8(1):69-78, 2010.
  5. Book: Sorin Draghici, Taghi M. Khoshgoftaar, Vasile Palade, Witold Pedrycz, M. Arif Wani, Xingquan Zhu (Eds.): The Ninth International Conference on Machine Learning and Applications, ICMLA 2010, Washington, DC, USA, 12-14 December 2010. IEEE Computer Society 2010, isbn 978-0-7695-4300-0.
  6. Peng Zhang, Xingquan Zhu, Jianlong Tan, and Li Guo, Classifier and Cluster Ensembling for Mining Concept Drifting Data Streams, Proceedings of the 10th IEEE International Conference on Data Mining (ICDM '10), Dec. 14-17, 2010, Sydney, Australia.
  7. Peng Zhang, Xingquan Zhu, Jianlong Tan, and Li Guo, SKIF: A Data Imputation Framework for Concept Drifting Data Streams, Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM-2010), Toronto, Canada, Oct. 26-30, 2010.
  8. Zhenfeng Zhu, Xingquan Zhu, Yuefei Guo, and Xiangyang Xue, Transfer Incremental Learning for Pattern Classification, Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM-2010), Toronto, Canada, Oct. 26-30, 2010.
  9. Zhengyu Lu, Xindong Wu, Xingquan Zhu, and Josh Bongard, Ensemble Pruning via Individual Contribution Ordering, Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '10), July 25-28, 2010, Washington, DC, USA.
  10. Dan He, Xindong Wu, and Xingquan Zhu, Rule Synthesizing from Multiple Related Databases, Proc. the 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-10), Hyderabad, India, June 2010.

2009

  1. X. Jiang and X. Zhu, vEye: Behavioral Footprinting for Self-Propagating Worm Detection and Profiling, Knowledge and Information Systems, 18(2):231-263, 2009.
  2. Xingquan Zhu, Xindong Wu, and Chengqi Zhang, Vague One-Class Learning for Data Streams, Proceedings of the 9th IEEE International Conference on Data Mining (ICDM '09), December 6-9, 2009, Miami, FL, USA.
  3. Peng Zhang, Xingquan Zhu, and Li Guo, Mining Data Streams with Labeled and Unlabeled Training Examples, Proceedings of the 9th IEEE International Conference on Data Mining (ICDM '09), December 6-9, 2009, Miami, FL, USA.
  4. Xingquan Zhu and Ruoming Jin, Multiple Information Sources Cooperative Learning, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI '09), July 11-17, 2009, Pasadena, California, USA.
  5. D. He, X. Zhu, and X. Wu, Approximate Repeating Pattern Mining with Gap Requirements, Proc. of the 21st IEEE International Conference on Tools with Artificial Intelligence (ICTAI-09), Newark, New Jersey, Nov. 2009.
  6. D. He, X. Zhu, and X. Wu, Error Detection and Uncertainty Modeling for Imprecise Data, Proc. of the 21st IEEE International Conference on Tools with Artificial Intelligence (ICTAI-09), Newark, New Jersey, Nov. 2009.
  7. A. Kamal, X. Zhu, A. Pandya, S. Hsu, Feature Selection with Biased Sample Distributions, Proc. of the IEEE International Conference on Information Reuse (IRI-09), Las Vegas, August, 2009.
  8. A. Kamal, X. Zhu, R. Narayanan, Gene Selection, for Microarray Expression Data with Imbalanced Sample Distributions, Proc. of the International Joint Conference on Bioinformatics, Systems Biology and Intelligence Computing (IJCBS-09), Shanghai, China, August, 2009.
  9. M. Slavik, X. Zhu, I. Mahgoub, and M. Shoaib, Parallel Selection of Informative Genes for Classification, Proc. Of the 1st International Conference on Bioinformatics and Computational Biology (BICoB-09), New Orleans, April, 2009.
  10. A. Kamal, X. Zhu, A. Pandya, S. Hsu, and M. Shoaib, The Impact of Gene Selection on Imbalanced Microarray Expression Data, Proc. Of the 1st International Conference on Bioinformatics and Computational Biology (BICoB-09), New Orleans, April, 2009.
  11. P. Zhang, X. Zhu, Y, Shi, and X. Wu, An Aggregate Ensemble for Mining Data Streams with both Concept Drifting and Noise, Proc. Of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09), Bangkok, April, 2009.

2008

  1. Xingquan Zhu and Ying Yang, A Lazy Bagging Approach to Classification, Pattern Recognition, 41(10): 2980-2992, October, 2008.
  2. Xindong Wu and Xingquan Zhu, Mining with Noise Knowledge: Error Awareness Data Mining, IEEE Transactions on Systems Man and Cybernetics, Part A, 38(4): 917-932, July, 2008.
  3. X. Zhu, R. Jin, Y. Breitbart, and G. Agrawal, MMIS-07, 08: Mining Multiple Information Sources Workshop Report, ACM SIGKDD Explorations, vol. 10, no.2, pp.61-65, Dec., 2008.
  4. X. Zhu, C. Zhang, and D. Olson, Editorial: Special Issue on Data Mining, International Journal of Software and Informatics, vol. 2, no.2, pp.89-94, Dec., 2008.
  5. Y. Yang, X. Wu, and X. Zhu, Conceptual equivalence for contrast mining in classification learning, Data and Knowledge Engineering, 67(3):413-429, Dec., 2008.
  6. G. Chen, X. Wu, and X. Zhu, Mining Sequential Patterns across Time Sequences, New Generation Computing, 26(1): 75-96, January, 2008
  7. Book Chapter: X. Zhu, Quantitative Association Rules, in Encyclopaedia of Database Systems, edited by Prof. Ling Liu and M. Tamer Oszu, Springer, 2008
  8. Book Chapter: X. Wu, Y. Zhang, and X. Zhu, Data Mining, in Encyclopaedia of Computer Science and Engineering, edited by Benjamin W. Wah, Wiley, 2008.
  9. Xingquan Zhu, Peng Zhang, Xindong Wu, Dan He, Chengqi Zhang, and Yong Shi, Cleansing Noisy Data Streams, Proceedings of the 8th IEEE International Conference on Data Mining (ICDM '08), December, 2008, Pisa, Italy.
  10. Peng Zhang, Xingquan Zhu, and Yong Shi, Categorizing and Mining Concept Drifting Data Stream, Proceedings of the 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '08), August, 2008, Las Vegas, USA.
  11. X. Zhu, C. Bao, W. Qiu, Bagging Very Weak Learners with Lazy Local Learning, Proc. Of the 19th International Conference on Pattern Recognition (ICPR), Tampa, Florida, December, 2008.
  12. P. Zhang, Y. Tian, Z. Zhang, A. Li, and X. Zhu, Select Objective Functions for Multiple Criteria Programming Classification, Proc. of IEEE/WIC/ACM Joint International Conference on Web Intelligence (WI) and Intelligent Agent Technology (IAT)), Sydney, Australia, December, 2008.
  13. X. Su, T. Khoshgoftaar, X. Zhu, VoB: Voting on Bagging Classifications, Proc. Of the 19th International Conference on Pattern Recognition (ICPR), Tampa, Florida, December, 2008.
  14. A. Kamal, X. Zhu, A. Pandya, S. Hsu, Y. Shi, An Empirical Study of Supervised Learning for Biological Sequence Profiling and Microarray Expression Data Analysis, Proc. Of the 2008 IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, July, 2008.
  15. X. Su, T. M. Khoshgoftaar, X. Zhu, VCI Predictors: Voting on Classifications from Imputed Learning Sets, Proc. Of the 2008 IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, July, 2008.
  16. C. Shah, X. Zhu, K. Khoshgoftaar, J. Beyer, Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction, Proc. of the 21st Florida Artificial Intelligence Research Society International Conference (FLAIRS), Florida, May, 2008.
  17. Y. Lee, X. Zhu, A. Pandya, S. Hsu, iVESTA: An Interactive Visualization and Evaluation System for Drive Test Data, Proc. of the 23rd ACM Symposium on Applied Computing (SAC) , Brazil, March, 2008.
  18. X. Su, T.M. Khoshgoftaar, X. Zhu, R. Greiner, Imputation-Boosted Collaborative Filtering Using Machine Learning Classifiers, Proc. of the 23rd Annual ACM Symposium on Applied Computing (SAC), Brazil, March, 2008.

2007

  1. Book: X. Zhu and I. Davidson, Knowledge Discovery and Data Mining: Challenges and Realities with Real World Data, Idea Group Inc. Publishing, 2007.
  2. G. Mao, X. Wu, X. Zhu, G. Chen, and C. Liu, Mining maximal frequent itemsets from data streams, Journal of Information Science, 33: 251-262, June 2007.
  3. X. Zhu, T. Khoshgoftaar, I. Davidson, and S. Zhang, Editorial: Special issue on mining low-quality data, Knowledge and Information Systems, 11(2): 131-136, February, 2007.
  4. Xingquan Zhu, Lazy Learning for Classifying Imbalanced Data, Proceedings of the 7th IEEE International Conference on Data Mining (ICDM '07), October 28-31, 2007, Omaha, USA.
  5. Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, Active Learning from Data Streams, Proceedings of the 7th IEEE International Conference on Data Mining (ICDM '07), October 28-31, 2007, Omaha, USA.
  6. Xingquan Zhu and Xindong Wu, Discovering Relational Patterns across Multiple Databases, Proceedings of the 23rd IEEE International Conference on Data Engineering (ICDE '07), April 15-20, 2007, Istanbul, Turkey.
  7. Xingquan Zhu, Xindong Wu, Taghi Khoshgoftaar, and Yong Shi, An Empirical Study of the Noise Impact on Cost-Sensitive Learning, Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI '07), January 6-12, 2007, Hyderabad, India.
  8. Xingquan Zhu and Xindong Wu, Mining Complex Patterns across Sequences with Gap Requirements, Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI '07), January 6-12, 2007, Hyderabad, India.
  9. X. Su, R. Greiner, T. Khoshgoftaar, X. Zhu, Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts, Proc. of Web Intelligence (WI), 645-649, 2007.
  10. X. Su, T. Khoshgoftaar, X. Zhu, A. Folleco, Rule-Based Multiple Object Tracking for Traffic Surveillance Using Collaborative Background Extraction, Proc. of International Symposium on Visual Computing (ISVC), (2), 469-478, 2007.
  11. D. He, X. Wu, and X. Zhu, SAIL-APPROX: An Efficient On-line Algorithm for Approximate Pattern Matching with Wildcards and Length Constraints, Proc. of the 2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), CA, November 2007.
  12. Y. He, X. Wu, X. Zhu, and A. N. Arslan, Mining Frequent Patterns with Wildcards from Biological Sequences, Proc. of the 2007 IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, August 2007, USA
  13. J. Wang, Y. Liu, L. Zhou, Y. Shi, and X. Zhu, Pushing Frequency Constraint to Utility Mining Model. Proc. of the International Conference on Computational Science (ICCS), pp.685-692, May 27-30, 2007.
  14. 57. Y. Liu, P. Scheuermann, X. Li, and X. Zhu: Using WordNet to Disambiguate Word Senses for Text Classification. Proc. of the International Conference on Computational Science (ICCS), pp.781-789, May 27-30, 2007.

2006

  1. Xingquan Zhu and Xindong Wu, Class Noise Handling for Effective Cost-Sensitive Learning by Cost-Guided Iterative Classification Filtering, IEEE Transactions on Knowledge and Data Engineering, 18(10): 1435-1440, November, 2006.
  2. Y. Yang, X. Wu, and X. Zhu, Mining in Anticipation for Concept Change: Proactive-Reactive Prediction in Data Streams, Data Mining and Knowledge Discovery, 13(3), November, 2006.
  3. G. Chen, X. Wu, X. Zhu, A. Arslan, and Y. He, Efficient string matching with wildcards and length constraints, Knowledge and Information Systems, 10(4): 399-419, November, 2006.
  4. X. Zhu, X. Wu, and Q. Chen, Bridging Local and Global Data Cleansing: Identifying Class Noise in Large, Distributed Data Datasets, Data Mining and Knowledge Discovery, 12(2-3), May 2006.
  5. X. Zhu, X. Wu, and Y. Yang, Effective Classification of Noisy Data Streams with Attribute-Oriented Dynamic Classifier Selection, Knowledge and Information Systems (KAIS), 9(3), 2006.
  6. Y. Zhang, X. Zhu, and X. Wu: Corrective Classification: Classifier Ensembling with Corrective and Diverse Base Learners. Proc. of the 6th IEEE International Conference on Data Mining (ICDM), pp.1199-1204, 18-22 December, 2006, Hong Kong.
  7. X. Zhu and X. Wu: Scalable Representative Instance Selection and Ranking. Proc. of the 18th International Conference on Pattern Recognition (ICPR), vol.3, pp.352-355, 20-24 August, 2006, Hong Kong.
  8. X. Jiang, Y. Motai, R. Snapp, and X. Zhu: Accelerated Kernel Feature Analysis. Proc. of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp.109-116, 17-22 June 2006, New York, USA.
  9. X. Zhu and X. Wu, Error Awareness Data Mining, Proc. of the IEEE International Conference on Granular Computing (GRC) , Atlanta, May 10-12, 2006,

2005

  1. Xingquan Zhu, Xindong Wu, Ahmed Elmagarmid, Zhe Feng, and Lide Wu, Video Data Mining: Semantic Indexing and Event Detection from the Association Perspective, IEEE Transactions on Knowledge and Data Engineering, 17(5): 665-677, May, 2005.
  2. Xingquan Zhu and Xindong Wu, Cost-Constrained Data Acquisition for Intelligent Data Preparation, IEEE Transactions on Knowledge and Data Engineering, 17(11): 1542-1556, November, 2005.
  3. Xingquan Zhu, Ahmed Elmagarmid, Xiangyang Xue, Lide Wu, and Ann Catlin, InsightVide: Towards Hierarchical Video Content Organization for Efficient Browsing, Summarization and Retrieval, IEEE Transactions on Multimedia, 7(4): 648-666, November, 2005.
  4. G. Chen, X. Wu, and X. Zhu, Sequential Pattern Mining in Multiple Data Streams, Proc. of the Fifth IEEE International Conference on Data Mining (ICDM '05), Houston, TX, USA, 27 - 30 November 2005.
  5. Y. Zhang, X. Zhu, X. Wu, and J. P. Bond, ACE: An Aggressive Classifier Ensemble with Error Detection, Correction and Cleansing, Proc. of the 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Hong Kong, November 14-16, 2005. (Best Paper Award)
  6. Y. Yang, X. Wu, and X. Zhu, Mining in Anticipation: Proactive-Reactive Prediction for Data Streams, Proc. of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Chicago, IL, USA, August 21-24, 2005.
  7. X. Jiang, Y. Motai, and X. Zhu, Predictive Fuzzy Control For A Mobile Robot With Nonholonomic Constraints, In Proceedings of the 12th International Conference on Advanced Robotics (ICAR 2005), Seattle, Washington, USA, July 18th-20th, 2005.
  8. Q. Chen, X. Wu, and X. Zhu, “Scalable Inductive Learning on Partitioned Data”, In Proceedings of the 15th International Symposium on Methodologies for Intelligent Systems (ISMIS 2005), Saratoga Springs, NY, May 26 - 28, 2005.

2004

  1. Xingquan Zhu and Xindong Wu, Class Noise vs. Attribute Noise: A Quantitative Study of Their Impacts, Artificial Intelligence Review, 22 (3-4):177-210, November 2004.
  2. X. Zhu, X. Wu, J. Fan, A. Elmagarmid, and W. Aref, Exploring video content structure for hierarchical summarization, ACM / Springer Multimedia System Journal, 10(2):98-115, 2004.
  3. W. Aref, A. Catlin, A. Elmagarmid, J. Fan, M. Hammad, I. Ilyas, M. Marzouk, S. Prabhakar, and X. Zhu, A testbed facility for research in video database benchmarking, ACM / Springer Multimedia System Journal, Special Issue on Multimedia Document Management Systems, vol.9, no.6, 2004.
  4. J. Fan, A. Elmagarmid, X. Zhu, W. Aref, and L. Wu, ClusterView: Hierarchical Video Shot Classification, indexing and accessing, IEEE Trans. on Multimedia, pp.70-86, vol.6, no.1, 2004.
  5. Book Chapter: J. Fan, X. Zhu, J. Xiao, Content-Based Video Retrieval, in Computer Graphics and Multimedia: Applications, Problems and Solutions, edited by Prof. John DiMarco, Idea Group Pub, Feb.,2004
  6. X. Zhu, X. Wu and Y. Yang, Dynamic Classifier Selection for Effective Mining from Noisy Data Streams, Proc. of the 4th IEEE International Conference on Data Mining (ICDM 2004), UK, 2004.
  7. X. Zhu and X. Wu, Cost-guided Class Noise Handling for Effective Cost-sensitive Learning, Proc. of the 4th IEEE International Conference on Data Mining (ICDM 2004), UK, 2004.
  8. Y. Yang, X. Wu, X. Zhu, Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources, Proc. of 8th PKDD-2004, Pisa, Italy, 2004.
  9. X. Zhu, X. Wu, Y. Yang, Error detection and impact-sensitive instance ranking in noisy datasets, Proc. of the 19th National Conference on Artificial Intelligence (AAAI-2004), July 25-29, California.
  10. X. Zhu and X. Wu, Data Acquisition with Active and Impact-Sensitive Instance Selection, Proc. of the 16th IEEE International Conf. on Tools with Artificial Intelligence (ICTAI 2004), FL, 2004.
  11. Q. Chen, X. Wu, X. Zhu, OIDM: Online Interactive Data Mining, Proc. of the 17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-2004), May 17-20, 2004, Ottawa, Canada.

2003

  1. Xingquan Zhu, Jianping Fan, Ahmed Elmagarmid, and Xindong Wu, Hierarchical Video Summarization and Content Description Joint Semantic and Visual Similarity, ACM / Springer Multimedia System Journal, 9(1):31-53, 2003.
  2. E. Bertino, J. Fan, E. Ferrari, M.S. Hacid, A.K. Elmagarmid, and X. Zhu, A Hierarchical Access Control Model for Video Database Systems, ACM Trans. on Information Systems, 21(2), pp.155-191, 2003.
  3. J. Fan, X. Zhu, K. Najarian, and L. Wu, Accessing video contents through key objects over IP, Journal of Multimedia Tools and Applications, vol.21, no.1, pp.75-96, 2003.
  4. X. Zhu, X. Wu, Q. Chen, Eliminating class noise in large datasets, Proc. of the 20th ICML International Conference on Machine Learning (ICML-2003), Aug. 21-24, Washington D.C., 2003.
  5. X. Zhu, X. Wu, Mining video association for efficient database management, Proc. of the 18th International Joint Conference on Artificial Intelligence (IJCAI-2003), Acapulco, Mexico. Aug.,12 -15, pp.1422-1424, 2003.
  6. X. Zhu, X. Wu, Sequential association mining for video summarization, Proc. of IEEE International Conference on Multimedia & Expo (ICME-2003), Baltimore, MD. July, 6-9, 2003.
  7. H. Luo, J. Fan, J. Xiao, X. Zhu, Semantic principal video shot classification via mixture Gaussian, Proc. of IEEE International Conf. on Multimedia & Expo (ICME 2003), MD. July, 6-9, 2003.
  8. X. Zhu, W. G. Aref, J. Fan, A. C. Catlin, A. K. Elmagarmid, Medical video mining for efficient database indexing, management and access, Proc. of the 19th IEEE International Conference on Data Engineering (ICDE-2003), India, March, 2003.
  9. W. Aref,A. Catlin, A. K. Elmagarmid, J. Fan, M. Hammad, I. Ilyas, M. Marzouk, S. Prabhakar, Y. Tu, X. Zhu, " VDBMS: A testbed facility for research in video database benchmark ", (invited paper), 9th International Conference on Distributed Multimedia Systems, Miami, Sept. 23-25, 2003.

2002

  1. J. Fan, X. Zhu, M.S. Hacid, and A. K. Elmagarmid, Content-based video classification toward hierarchical representation, indexing and accessing, Journal of Multimedia Tools and Applications, special issue on multimedia and internet, Vol. 17, No. 1, pp.97-120, 2002.
  2. X. Zhu, J. Fan, H. Luo, M.S. Hacid, Using small samples for content-based image retrieval system with relevance feedback, Proc. of ACM Multimedia Workshop on Multimedia Information Retrieval (MIR-2002), Juan Les Pins, France, Dec., 2002.
  3. J. Fan, H. Luo, X. Zhu, Semantic principal video shot classification system, Proc. of ACM Multimedia Workshop on Multimedia Information Retrieval (MIR-2002), Juan Les Pins, France, Dec., 2002.
  4. X. Zhu, J. Fan, M.S. Hacid, A. K. Elmagarmid, ClassMiner: Mining medical video for scalable skimming and summarization, Proc. of 10th ACM International Conference on Multimedia, pp.79-80, France, Dec., 2002
  5. X. Zhu, J. Fan, X. Xue, L. Wu, A. K. Elmagarmid, Semi-automatic video annotation, Proc. of Third IEEE Pacific Rim Conference on Multimedia (PCM-2002), LNCS 2532, Springer, pp.245-252, Taiwan, Dec., 2002.
  6. X. Zhu, X. Xue, J. Fan, L. Wu, Qualitative camera motion classification for content-based video indexing, Proc. of Third IEEE Pacific Rim Conference on Multimedia (PCM-2002), LNCS 2532, pp.1128-1136, Taiwan, Dec., 2002.
  7. X. Zhu, J. Fan, W. G. Aref, A. K. Elmagarmid, ClassMiner: Mining medical video content structure and events towards efficient access and scalable skimming, Proc. of ACM SIGMOD Workshop on Data Mining and Knowledge Discovery (DMKD-2002), pp.9-19, June, Madison, WI, 2002
  8. X. Xue, X. Zhu, Y. Xiao, L. Wu, Using mutual relationship between motion vectors for qualitative camera motion classification in MPEG video. Proc. of SPIE: Second International Conference on Image and Graphics (ICIG-2002), Vol.4875, pp.853-860, Anhui, Aug., 2002.
  9. X. Zhu, J. Fan, A. K. Elmagarmid, Towards facial feature locating and verification for omni-face detection in video/images, Proc. of IEEE International Conference on Image Processing (ICIP-2002), vol.2, pp.113-116, NY, Sept., 2002.
  10. X. Zhu, J. Fan, A. K. Elmagarmid, W. G. Aref, Hierarchical video summary for medical data, Proc. SPIE: Storage and Retrieval for Media Databases 2002 (SPIE-2002), vol. 4676, pp.395-406, San Jose, Jan. 2002
  11. J. Fan, M. Body, X. Zhu, M.S. Hacid, Seeded image segmentation for content-based image retrieval application, Proc. SPIE: Storage and Retrieval for Media Databases 2002 (SPIE-2002), vol.4676, pp.10-21, San Jose, Jan. 2002.
  12. X. Lu, Z. Feng, X. Zhu, L. Wu, News story segmentation based on a simple statistic model, Proc SPIE: Internet Imaging III 2002 (SPIE-2002), vol.4672, pp.261-268, San Jose, Jan 2002
  13. W.G. Aref, A. Catlin, A.K. Elmagarmid, J. Fan, M. Hammad, I. Ilyas, M. Marzouk, X. Zhu A video database management system for advancing video database research, International Workshop on Multimedia Information Systems (MIS-2002), Tempe, Arizona, USA, Oct.30-Nov.1, 2002.
  14. W. G. Aref, A.C. Catlin, A. K. Elmagarmid, J. Fan, J. Guo, M. Hammad, I.F. Ilyas, M.S. Marzouk, S. Prabhakar, A. Rezgui, S. Teoh, E. Terzi, Y. Tu, A. Vakali, X. Zhu, A Distributed Database Server for Continuous Media, 18th IEEE International Conference on Data Engineering (ICDE-2002), pp. 490-491, San Jose, California.

2001

  1. Xingquan Zhu, Hongjiang Zhang, Wenying Liu, Chunhui Hu, and Lide Wu, A new query refinement and semantics integrated image retrieval system with semi-automatic annotation scheme, Journal of Electronic Imaging, Special Issue on Storage, Processing and Retrieval of Digital Media, Vol.10 (4), pp.850-850, 2001.
  2. Jianping Fan, Xingquan Zhu, and Lide Wu, Automatic model-based semantic object extraction algorithm, IEEE Trans. on Circuits and Systems for Video Technology, vol.11, no.10, pp.1073-1084, Oct., 2001.
  3. Jianping Fan, Walid G. Aref, Ahmed K. Elmagarmid, M.S. Hacid, M.S. Marzouk, and Xingquan Zhu, MultiView: multi-level video content representation and retrieval, Journal of Electronic Imaging, Special Issue on Storage, Processing and Retrieval of Digital Media, Vol. 10 (4). 2001.
  4. Xingquan Zhu, Lide wu, Xiangyang Xue, Xiaoye Lu, and Jianping Fan, Automatic Scene Detection in News Program by Integrating Visual Feature and Rules, Proc. of the second IEEE Pacific-Rim conference on multimedia (PCM-2001), LNCS2195 , Springer, pp.837-842, Beijing, Oct. 24-26, 2001.
  5. Jianping Fan, Xingquan Zhu, and Lide Wu, Seeded Semantic Object Generation Toward Content-Based Video Indexing, Proc. of the second IEEE Pacific-Rim conference on multimedia (PCM-2001), LNCS2195, Springer, pp. 843-848, Beijing, Oct. 24-26, 2001.
  6. Xingquan Zhu, Wenying Liu, Hongjiang Zhang, and Lide Wu, An image retrieval and semi-automatic annotation scheme for large image databases on the Web, Proc. 13th SPIE symposium on Electronic Imaging-EI24 Internet Imaging II (SPIE-2001), Vol.4311, pp.168-177 Jan. 2001, San Jose.

2000

  1. Ye Lu, Chunhui Hu, Xingquan Zhu, Hongjiang Zhang, and Qiang Yang, A Unified Semantics and Feature Based Image Retrieval Technique Using Relevance Feedback, Proc. of the 8th ACM International Conference on Multimedia (ACM MM-2000), pp. 31 - 37 LA, California, October, 2000.