Publication

2009¶

• Z.-H. Zhou and T. Washio, eds. Advances in Machine Learning (Lecture Notes in Artificial Intelligence 5828). Proceedings of the 1st Asian Conference on Machine Learning (ACML'09), Berlin: Springer, 2009. ISBN: 978-3-642-05223-1

• G. Tsoumakas, M.-L. Zhang, and Z.-H. Zhou, eds. Working Notes of the 1st Workshop on Learning from Multi-Label Data (MLD'09), in conjunction with ECML PKDD'09, Bled, Slovenia, 2009.

• N. Chawla, N. Japkowicz, and Z.-H. Zhou, eds. Working Notes of the Workshop on Data Mining When Classes are Imbalanced and Errors Have Costs (ICEC'09), in conjunction with PAKDD'09, Bangkok, Thailand, 2009.

• Z.-H. Zhou, H. Li, and Q. Yang. Editorial: Special issue on selected papers of PAKDD 2007. Knowledge and Information Systems, 2009, 19(2): 131-132.

• T. B. Ho, Z.-H. Zhou, and H. Motoda. Preface. International Journal of Software and Informatics, 2009, 3(1): 1-2.

• Z.-H. Zhou. Ensemble learning. In: S. Z. Li ed. Encyclopedia of Biometrics, Berlin: Springer, 2009, 270-273.

• Z.-H. Zhou. Ensemble. In: L. Liu and T. Özsu eds. Encyclopedia of Database Systems, Berlin: Springer, 2009, 988-991.

• Z.-H. Zhou. Boosting. In: L. Liu and T. Özsu eds. Encyclopedia of Database Systems, Berlin: Springer, 2009, 260-263.

• Z.-H. Zhou and Y. Yu. AdaBoost. In: X. Wu and V. Kumar eds. The Top Ten Algorithms in Data Mining, Boca Raton, FL: Chapman & Hall, 2009, 127-149.

• X.-B. Xue and Z.-H. Zhou. Distributional features for text categorization. IEEE Transactions on Knowledge and Data Engineering, 2009, 21(3): 428-442.

• Y. Guo, F. Liu, J. Shi, Z.-H. Zhou, and M. Gleicher. Image retargeting using mesh parametrization. IEEE Transactions on Multimedia, 2009, 11(5): 856-867.

• X. Tan, S. Chen, Z.-H. Zhou, and J. Liu. Face recognition under occlusions and variant expressions with partial similarity. IEEE Transactions on Information Forensics & Security, 2009, 4(2): 217-230.

• X.-Y. Liu, J. Wu, and Z.-H. Zhou. Exploratory undersampling for class-imbalance learning_. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2009, 39(2): 539-550.

• M. Li, H. Li, and Z.-H. Zhou. Semi-supervised document retrieval. Information Processing & Management, 2009, 45(3): 341-355.

• M.-L. Zhang and Z.-H. Zhou. Multi-instance clustering with applications to multi-instance prediction. Applied Intelligence, 2009, 31(1): 47-68.

• S. Ji, Y.-X. Li, Z.-H. Zhou, S. Kumar, J. Ye. A bag-of-words approach for drosophila gene expression pattern annotation. BMC Bioinformatics, 2009, 10: 119.

• Y. Jiang, M. Li, and Z.-H. Zhou. Mining extremely small data sets with application to software reuse. Software: Practice and Experience, 2009, 39(4): 423-440.

• N. Li, Y. Yu, and Z.-H. Zhou. Semi-naive exploitation of one-dependence estimators. In: Proceedings of the 9th IEEE International Conference on Data Mining (ICDM'09), Miami, FL, 2009, pp.278-287.

• L.-P. Liu, Y. Jiang, and Z.-H. Zhou. Least square incremental linear discriminant analysis. In: Proceedings of the 9th IEEE International Conference on Data Mining (ICDM'09), Miami, FL, 2009, pp.298-306.

• X. Geng, K. Smith-Miles, Z.-H. Zhou, and L. Wang. Face image modeling by multilinear subspace analysis with missing values. In: Proceedings of the 17th ACM International Conference on Multimedia (ACM Multimedia'09), Beijing, China, 2009, pp.629-632. (short paper)

• Y.-F. Li, J. T. Kwok, I. W. Tsang, and Z.-H. Zhou. A convex method for locating regions of interest with multi-instance learning. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'09), Bled, Slovenia, Part II, LNAI 5782, 2009, pp.15-30.

• J.-M. Xu, G. Fumera, F. Roli, and Z.-H. Zhou. Training SpamAssassin with active semi-supervised learning. In: Proceedings of the 6th Conference on Email and Anti-Spam (CEAS'09), Mountain View, CA, 2009.

• Z.-H. Zhou, Y.-Y. Sun, and Y.-F. Li. Multi-instance learning by treating instances as non-i.i.d. samples. In: Proceedings of the 26th International Conference on Machine Learning (ICML'09), Montreal, Canada, 2009, pp.1249-1256. (CORR abs/0807.1997)

• Y.-F. Li, J. T. Kwok, and Z.-H. Zhou. Semi-supervised learning using label mean. In: Proceedings of the 26th International Conference on Machine Learning (ICML'09), Montreal, Canada, 2009, pp.633-640.

• D.-C. Zhan, M. Li, Y.-F. Li, and Z.-H. Zhou. Learning instance specific distances using metric propagation. In: Proceedings of the 26th International Conference on Machine Learning (ICML'09), Montreal, Canada, 2009, pp.1225-1232.

• S. Ji, L. Yuan, Y.-X. Li, Z.-H. Zhou, S. Kumar, and J. Ye. Drosophila gene expression pattern annotation using sparse features and term-term interactions. In: Proceedings of the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'09), Paris, France, 2009, pp.407-416.

• Y. Zhang and Z.-H. Zhou. Non-metric label propagation. In: Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), Pasadena, CA, 2009, pp.1357-1362.

• M. Li, X.-B. Xue, and Z.-H. Zhou. Exploiting multi-modal interactions: A unified framework. In: Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), Pasadena, CA, 2009, pp.1120-1125.

• Y.-X. Li, S. Ji, J. Ye, S. Kumar, and Z.-H. Zhou. Drosophila gene expression pattern annotation through multi-instance multi-label learning. In: Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), Pasadena, CA, 2009, pp.1445-1450.

• Z.-H. Zhou. When semi-supervised learning meets ensemble learning. In: Proceedings of the 8th International Workshop on Multiple Classifier Systems (MCS'09), Reykjavik, Iceland, LNCS 5519, 2009, pp.529-538. Invited plenary talk at MCS'09

• N. Li and Z.-H. Zhou. Selective ensemble under regularization framework. In: Proceedings of the 8th International Workshop on Multiple Classifier Systems (MCS'09), Reykjavik, Iceland, LNCS 5519, 2009, pp.293-303.

• R. Jin, S. Wang, and Z.-H. Zhou. Learning a distance metric from multi-instance multi-label data. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'09), Miami, FL, 2009, pp.896-902.

• X. Tan, F. Song, Z.-H. Zhou, and S. Chen. Enhanced pictorial structures for precise eye localization under uncontrolled conditions. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'09), Miami, FL, 2009, pp.1621-628.

• Y.-F. Li, I. W. Tsang, J. Kwok, and Z.-H. Zhou. Tighter and convex maximum margin clustering. In: Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS'09), Clearwater Beach, FL, 2009, pp.328-335.

• Z.-H. Zhou, M. Ng, Q.-Q. She, and Y. Jiang. Budget semi-supervised learning. In: Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'09), Bangkok, Thailand, LNAI 5476, 2009, pp.588-595.

• C. X. Ling, J. Du, and Z.-H. Zhou. When does co-training work in real data? In: Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'09), Bangkok, Thailand, LNAI 5476, 2009, pp.596-603.

• X.-Y. Liu and Z.-H. Zhou. Learning with cost intervals. In: Working Notes of the Workshop on Data Mining When Imbalanced Classes and Errors in Costs (ICEC'09), in conjunction with PAKDD'09, Bangkok, Thailand, 2009, pp.26-37.

• 周志华, 王珏 主编. 机器学习及其应用:2009, 北京: 清华大学出版社, 2009. (ISBN 978-7-302-20419-0)

• 周志华, 张敏灵. MIML: 多示例多标记学习. 见: 周志华, 王珏 主编, 机器学习及其应用:2009, 北京: 清华大学出版社, 2009, 218-234 (第10章).