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Book Chapter

  • Zhi-Hua Zhou and Yang Yu. The AdaBoost algorithm. In: X. Wu and V. Kumar eds. The Top Ten Algorithms in Data Mining, Boca Raton, FL: Chapman & Hall, 2009. (PDF)

Journal Articles

  • Yang Yu and Zhi-Hua Zhou. A framework for modeling positive class expansion with single snapshot. Knowledge and Information Systems, 2010, 25(2):211-227. (Extended from PAKDD'08) (PDF) (slides) (code&data)

  • Fei Tony Liu, Kai Ming Ting, Yang Yu, and Zhi-Hua Zhou . Spectrum of variable-random trees. Journal of Artificial Intelligence Research, 2008, 32:355-384. (PDF)

  • Yang Yu, De-Chuan. Zhan, Xu-Ying Liu, Ming Li, and Zhi-Hua Zhou. Predicting future customers via ensembling gradually expanded trees. International Journal of Data Warehousing and Mining, 2007 3(2): 12-21. Invited paper for the PAKDD'06 Data Mining Competition (Open Category) Grand Champion Team (PDF)

  • Zhi-Hua Zhou and Yang Yu. Ensembling local learners through multi-modal perturbation. IEEE Transactions on System, Man, And Cybernetics - Part B: Cybernetics, 2005, 35(4): 725-735. (PDF) (code)

  • Zhi-Hua Zhou and Yang Yu. Adapt bagging to nearest neighbor classifiers. Journal of Computer Science and Technology, 2005, vol.20, no.1 pp.48-54. (PDF) (detailed result)

Conference Papers

  • Nan Li, Yang Yu, and Z.-H. Zhou. Diversity Regularized Ensemble Pruning. In: Proceedings of the 23rd European Conference on Machine Learning (ECML'12), Bristol, U.K., 2012.

  • Sheng-Jun Huang, Yang Yu, and Z.-H. Zhou. Multi-label hypothesis reuse. In: Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, 2012. (PDF) (code)

  • Sheng-Jun Huang, Yang Yu and Zhi-Hua Zhou, Multi-label boosting via hypothesis reuse. In: Proceedings of NIPS Workshop on Chanllenges in Learning Hierarchical Models: Transfer Learning and Optimization, Granada, Spain 2011.

  • Yang Yu, Yu-Feng Li, and Zhi-Hua Zhou. Diversity Regularized Machine In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI'11), Barcelona, Spain, 2011, pp. 1603-1608. (PDF)

  • Nan Li, Yang Yu, and Zhi-Hua 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. (PDF)

  • Yang Yu and Zhi-Hua Zhou. A framework for modeling positive class expansion with single snapshot. In: Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'08), Osaka, Japan, LNAI 5012, 2008, pp.429-440. (PDF) (slides) (This paper won the Best Paper Award at PAKDD'08)

  • Li-Ping Liu, Yang Yu, Yuan Jiang, and Zhi-Hua Zhou. TEFE: A Time-Efficient Approach to Feature Extraction. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), Pisa, Italy, 2008, pp.423-432. (PDF)

  • Yang Yu, Zhi-Hua Zhou, and Kai Ming Ting. Cocktail ensemble for regression. In: Proceedings of the 7th IEEE International Conference on Data Mining (ICDM'07), Omaha, NE, 2007, pp.721-726. (PDF)

Thesis

  • Yang Yu. Local Validity Based Selective Ensemble of Decision Trees. B.Sc. Thesis, 2004. (in Chinese with English abstract) (PDF)
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