Papers in Peer-Refereed Journals

  • L. Jiang, Z. Cai, H. Zhang, and D. Wang, Naive Bayes Text Classifiers: A Locally Weighted Learning Approach, Journal of Experimental & Theoretical Artificial Intelligence , Accepted.
  • L. Jiang, Z. Cai, H. Zhang, and D. Wang, Not so greedy: Randomly Selected Naive Bayes, Expert Systems with Applications, 2012, 39(12): 11022-11028.
  • L. Jiang, H. Zhang, Z. Cai, and D. Wang, Weighted Average of One-Dependence Estimators, Journal of Experimental & Theoretical Artificial Intelligence, 2012, 24(2): 219-230
  • L. Jiang, Z. Cai, D. Wang, and H. Zhang, Improving Tree Augmented Naive Bayes for Class Probability Estimation, Knowledge-Based Systems, 2012, 26: 239-245.
  • Z. Cai, W. Gong, C. X. Ling, H. Zhang, A clustering-based differential evolution for global optimization, Applied Soft Computing, 11(1): 1363-1379 (2011)
  • H. Liang, Y. Yan, H. Zhang, Learning Decision Trees with log Conditional Likelihood, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 24, No. 1 (2010)
  • L. Jiang, H. Zhang and Z. Cai, A Novel Bayes Model: Hidden Naive Bayes, IEEE Tran. on Knowledge and Data Engineering, Vol. 10, 2009.
  • L. Jiang, D. Wang, H. Zhang, et al., Using Instance cloning to Improve Naive Bayes for Ranking, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 6 (2008).
  • W. Wei, C. M. Li and H. Zhang, A Switching Criterion for Intensification and Diversification in Local Search for SAT, Journal on Satisfiability, Boolean Modeling and Computation, Vol.4 (2008).
  • H. Zhang and Jiang Su, Naive Bayes for Optimal Ranking. Journal of Experimental & Theoretical Artificial Intelligence , Vol.20, No. 2 (2008).
  • H. Zhang and Jiang Su, Learning probabilistic decision trees for AUC. Pattern Recognition Letters. Vol.27(2006).
  • H. Zhang, Exploring conditions for the optimality of naive Bayes. International Journal of Pattern Recognition and Artificial Intelligence, Vol. 19, No. 2 (2005).
  • Y. Wang, B. Spencer, H. Zhang and Y. Yan, , A text categorization approach for match-making in online business tendering. Journal of Business and Technology, 2005.
  • H. Zhang and C.X. Ling, Numerical mapping and learnability of naive Bayes. Applied Artificial Intelligence. Vol.17, No.5-6, 2003.
  • C. X. Ling and H. Zhang, The representational power of discrete Bayesian networks. Journal of Machine Learning Research . Vol.3(2002).
  • C. X. Ling, J. Gao, H. Zhang, et al., Improving Encarta search engine performance by mining user logs. International Journal of Pattern Recognition and Artificial Intelligence. Vol.16, No.18, 2002.
    • Papers in Peer-Refereed Conference Proceedings

    2012
  • Y. Guo, H. Zhang, B. Spencer, Cost-Sensitive Self-Training, Proceedings of the 25th Canadian Conference on Artificial Intelligence (CAI2012).

    2011
  • Y. Guo, H. Zhang, X. Liu, Instance Selection in Semi-supervised Learning, Proceedings of the 24th Canadian Conference on Artificial Intelligence (CAI2011).
  • B. Wang, H. Zhang, B. Spencer, Y. Guo, The Unsymmetrical-Style Co-training. The 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (2011).

    • 2010
  • Y. Guo, X. Niu, H. Zhang, An Extensive Empirical Study on Semi-supervised Learning, Proceedings of the 10th IEEE International Conference on Data Mining (ICDM 2010) (regular paper).
  • B. Wang and H. Zhang, Semi-supervised Probability Propagation on Instance-Attribute Graphs, Proceedings of the 23rd Canadian Conference on Artificial Intelligence (CAI2010), Springer (2010).

    • 2008
  • W. Wei, C. M. Li and H. Zhang, Switching among Non-Weighting, Clause Weighting, and Variable Weighting in Local Search for SAT, Proceedings of the International Conference on Principles and Practice of Constraint Programming (CP2008), Springer(2008).
  • J. Huang, C.X. Ling and H. Zhang, Proper Model Selection with Significance Test, Proceedings of the European Conference on Machine Learning (ECML-2008).
  • J. Su, H. Zhang, C.X. Ling and S. Matwin, Discriminative Parameter Learning for Bayesian Networks, Proceedings of the 25th International Conference on Machine Learning (ICML-2008).
  • B. Wang, B. Spencer, C.X. Ling and H. Zhang, Semi-supervised Self-training for Sentence Subjectivity Classification, Proceedings of the 21th Canadian Conference on Artificial Intelligence (CAI2008), Springer (2008).

    • 2007
  • C. M. Li and W. Wei and H. Zhang, Adaptive Noise and Look-Ahead in Local Search for SAT, Proceedings of the Tenth International Conference on Theory and Applications of Satisfiability Testing (SAT 2007), Springer(2007).
  • B. Wang and H. Zhang, Probability Based Metrics for Locally Weighted Naive Bayes, Proceedings of the 20th Canadian Conference on Artificial Intelligence (CAI2007), Springer (2007).
  • L. Jiang, H. Zhang, D, Wang, Z, Cai, Learning Locally Weighted C4.4 for Class Probability Estimation. Discovery Science 2007: 104-115

    • 2006
  • H. Liang, H. Zhang and Y. Yan, Decision Trees for Probability Estimation: An Empirical Study, to appear in Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI06), IEEE Computer Society Press(2006).
  • C. M. Li, W. Wei and H. Zhang, Combining Adaptive Noise and Look-Ahead in Local Search for SAT, The Third International Workshop on Local Search Techniques in Constraint Satisfaction in CP06 .
  • B. Wang and H. Zhang, Improving the Ranking Performance of Decision Trees, Proceedings of The 17th European Conference on Machine Learning (ECML06) , Springer(2006).
  • J. Su and H. Zhang, A Fast Decision Tree Learning Algorithm, Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06) , AAAI Press(2006).
  • J. Su and H. Zhang, Full Bayesian Network Classifiers, Proceedings of the 23rd International Conference on Machine Learning (ICML2006). .
  • L. Jiang and H. Zhang, Aggregating Weighted One-Dependence Estimators, Proceedings of the 9th Biennial Pacific Rim International Conference on Artificial Intelligence (PRICAI 2006), Springer(2006).
  • J. Su and H. Zhang, Probabilistic Inference Trees for Classification and Ranking, Proceedings of the Nineteenth Canadian Conference on Artificial Intelligence (CAI2006), Springer(2006).
  • L. Jiang and H. Zhang, Lazy Averaged One-Dependence Estimators, Proceedings of the Nineteenth Canadian Conference on Artificial Intelligence (CAI2006), Springer(2006).
  • L. Jiang and H. Zhang, Learning Naive Bayes for Probability Estimation by Feature Selection, Proceedings of the Nineteenth Canadian Conference on Artificial Intelligence (CAI2006), Springer(2006).
  • L. Jiang and H. Zhang, Dynamic K-nearest-neighbor Naive Bayes with Attribute Weighted, to appear in Proceedings of the Third International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'06) , Springer(2006).

    2005
  • L. Jiang and H. Zhang, Learning Instance Greedily Cloning Naive Bayes for Ranking, Proceeding of the Fifth IEEE International Conference on Data Mining (ICDM2005) , IEEE Computer Society Press(2005).
  • H. Zhang, L. Jiang and J. Su, Augmenting Naive Bayes for Ranking , Proceedings of 22nd International Conference on Machine Learning (ICML 2005) , ACM(2005).
  • J. Su and H. Zhang, Representing Conditional Independence Using Decision Trees, Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05) , AAAI Press(2005).
  • H. Zhang, L. Jiang and J. Su, Hidden Naive Bayes , Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05) , AAAI Press(2005).
  • L. Jiang, H. Zhang, Z. Cai and J. Su, Learning tree augmented naive Bayes for ranking , Proceedings of the 10th International Conference on Database Systems for Advanced Applications (DASFAA 2005). , Springer(2005).
  • L. Jiang, H. Zhang and J. Su, Instance Cloning Local Naive Bayes, Proceedings of the Eighteenth Canadian Conference on Artificial Intelligence (CAI2005), Springer(2005).
  • L. Jiang, H. Zhang, Z. Cai and J. Su, One Dependence Augmented Naive Bayes, Proceedings of First International Conference on Advanced Data Mining and Applications (ADMA2005), Springer(2005).
  • L. Jiang, H. Zhang and J. Su, Learning k-Nearest Neighbor Naive Bayes for Ranking, Proceedings of First International Conference on Advanced Data Mining and Applications (ADMA2005), Springer(2005).
  • L. Jiang, H. Zhang, Z. Cai and J. Su, Evolutional naive Baye, Proceedings of International Symposium on Intelligent Computation and its Applications (2005).

    2004
  • H. Zhang and J. Su, Naive Bayesian classifiers for ranking, Proceedings of the 15th European Conference on Machine Learning (ECML2004), Springer(2004).
  • H. Zhang and J. Su, Conditional independence trees, Proceedings of the 15th European Conference on Machine Learning (ECML2004), Springer(2004).
  • J. Su and H. Zhang, Learning conditional independence trees for ranking, Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM2004), IEEE Computer Society Press(2004).
  • H. Zhang and S. Sheng, Learning weighted naive Bayes with accurate ranking, Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM2004), IEEE Computer Society Press(2004).
  • H. Zhang, The optimality of naive Bayes, Proceedings of the 17th International FLAIRS conference (FLAIRS2004), Best paper award winner (second place), AAAI Press(2004).
  • Y. Wang, H. Zhang, B. Spencer and Y. Yan, Text categorization for an online tendering system, Proceedings of BASeWEB'04 (2004).

    2003
  • C. X. Ling, J. Huang and H. Zhang, AUC: a statistically consistent and more discriminating measure than accuracy, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI2003), Morgan Kaufmann(2003).
  • H. Zhang and C. X. Ling, A fundamental issue of naive Bayes, Proceedings of AI'2003, the Sixteenth Canadian Conference on Artificial Intelligence (CAI2003), Springer(2003).
  • C. X. Ling, J. Huang and H. Zhang, Comparing decision trees and naive Bayes using AUC , Proceedings of the Sixteenth Canadian Conference on Artificial Intelligence (CAI2003), Springer(2003).

    2002
  • H. Zhang and C. X. Ling, Representational upper bounds of Bayesian networks, Proceedings of the Nineteenth International Conference on Machine Learning (ICML2002), Morgan Kaufmann(2002).
  • C. X. Ling and H. Zhang, Toward Bayesian classifiers with accurate probabilities, Proceedings of the Sixth Pacific-Asia Conference on KDD (PAKDD2002), Springer(2002).

    2001
  • H. Zhang and C. X. Ling, Learnability of augmented naive Bayes in nominal domains, Proceedings of the Eighteenth International Conference on Machine Learning (ICML2001), Morgan Kaufmann (2001).
  • H. Zhang and C. X. Ling, Geometric properties of naive Bayes, Proceedings of the 12th European Conference on Machine Learning (ECML2001), Springer (2001).
  • H. Zhang and C. X. Ling, An improved learning algorithm for augmented naive Bayes, Proceedings of the Fifth Pacific-Asia Conference on KDD (PAKDD2001), Springer (2001).
  • C. X. Ling, J. Gao, H. Zhang, et al., Mining generalized query pattern from user logs, Proceedings of Hawaii International Conference on System Science, Hawaii, Jan. 2001.

    2000
  • H. Zhang and C. X. Ling, The learnability of naive Bayes, in Hamilton H. and Yang Q.(eds), Advances in Artificial Intelligence (Proceedings of CAI2000), Springer (2000).