2009

Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim, Most Relevant Explanation: Properties, Algorithms, and Evaluations, the 25th Conference on Uncertainty in Artificial Intelligence (UAI-09), June 18-21, Montreal, Canada. (Acceptance rate: poster, 31%)

Changhe Yuan, Eric Hansen, Efficient Computation of Jointree Bounds for Systematic MAP Search. Accepted by Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09). Pasadena, CA. 2009. (Acceptance rate: oral, 25%)

Changhe Yuan, Some Properties of Most Relevant Explanation, Twenty-First International Joint Conference on Artificial Intelligence ExaCt Workshop (ExaCt-09), Pasadena, CA. 2009.

2008

Changhe Yuan, Tsai-Ching Lu, A General Framework for Generating Multivariate Explanations in Bayesian Networks. In Proceedings of the Twenty-Third National Conference on Artificial Intelligence (AAAI-08). (Acceptance rate: oral, 24%)

Changhe Yuan, Eric Hansen, MAP Search in Bayesian Networks Using Joint Bounds. In Proceedings of AAAI-08 workshop on Search for Artificial Intelligence and Robotics. (Acceptance rate: oral, 43%)

Nan Wang, Changhe Yuan, Shane Burgess, Bindu Nanduri, Mark Lawrence, Susan Bridges, Integrating evidence for evaluation of potential novel protein-coding genes using Bayesian networks. Accepted to The 2008 International Conference on Bioinformatics & Computational Biology (BIOCOMP-08).

Changhe Yuan, Kui Xie, Xiaojian Wu, A Bayesian Approach for Motivational Diagnosis in Computer-Supported Collaborative Learning Environment. In Proceedings of International Symposium on Knowledge Acquisition and Modeling (KAM 2008). Dec., 2008.

2007

Changhe Yuan, and Marek J. Druzdzel, Generalized Evidence Pre-propagated Importance Sampling for Hybrid Bayesian Networks. In Proceedings of the Twenty-second National Conference on Artificial Intelligence (AAAI-07). (Acceptance rate: oral&poster, 5.1%)

Changhe Yuan, and Tsai-Ching Lu, Finding Explanations in Bayesian Networks. In Proceedings of the 18th International Workshop on Principles of Diagnosis (DX-07).

Changhe Yuan, and Marek J. Durzadzel, Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks. In Proceedings of the Twentieth Canadian Conference on Artificial Intelligence (AI-07). (Acceptance rate: oral, 17%)

Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan, Dynamic Weighting A* Search-Based MAP Algorithm for Bayesian Networks. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-07). Pages 2385-2390. 2007. (Acceptance rate: oral, 15.7%)

Changhe Yuan, and Marek J. Druzdzel, Importance Sampling for General Hybrid Bayesian Networks. In Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AISTAT-07).

Changhe Yuan, Marek J. Druzdzel, Theoretical Analysis and Practical Insights into Importance Sampling for Bayesian Networks. International Journal of Approximate Reasoning. Vol. 46, Pages 320-333, 2007.

2006

Changhe Yuan, Marek J. Druzdzel, Importance Sampling Algorithms for Bayesian Networks: Principles and Performance. Mathematical and Computer Modeling, Vol. 43, Pages 1189-1207, 2006.

Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan, Dynamic Weighting A* Search-Based MAP Algorithm for Bayesian Networks. In Proceedings of the Third European Workshop on Probabilistic Graphical Models (PGM-06), pages 279-286, Milan Studeny and Jiri Vomlel (eds.), Prague: Action M Agency, 2006.

Changhe Yuan, Marek J. Druzdzel, Hybrid Loopy Belief Propagation. In Proceedings of the Third European Workshop on Probabilistic Graphical Models (PGM-06), pages 317-324, Milan Studeny and Jiri Vomlel (eds.), Prague: Action M Agency, 2006.

2005 and Prior

Changhe Yuan, Importance Sampling for Bayesian Networks: Principles, Algorithms, and Performance. Ph.D. Dissertation, Intelligent Systems Program, University of Pittsburgh, 2006.

Changhe Yuan, Marek J. Druzdzel, Importance Sampling in Bayesian Networks: An Influence-Based Approximation Strategy for Importance Functions. In Proceedings of the 21st Annual Conference on Uncertainty in Artificial Intelligence (UAI-05). Pages 650-657. July 2005. (Acceptance rate: poster, 34%)

Changhe Yuan, Marek J. Druzdzel, How Heavy Should the Tails Be? In Proceedings of the 18th International Florida Artificial Intelligence Research Society Conference (FLAIRS-05). Pages 799-805. May 2005. (Acceptance rate: oral 53%)

Changhe Yuan, Marek J. Druzdzel, A Comparison on the Effectiveness of Two Heuristics for Importance Sampling. In Peter Lucas (Ed.): Proceedings of the Second European Workshop on Probabilistic Graphical Models (PGM-04), Leiden, October 2004, Pages 225-232.

Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel, Annealed MAP. In Proceedings of the 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI-04). Pages 628-635. July 2004. (Acceptance rate: oral, 10.4%)

Changhe Yuan, Marek J. Druzdzel, An Importance Sampling Algorithm Based on Evidence Pre-propagation. In Proceedings of the 19th Annual Conference on Uncertainty in Artificial Intelligence (UAI-03). Pages 624-631. August 2003. (Acceptance rate: poster 23%)

Changhe Yuan, EPIS-BN: An Importance Sampling Algorithm Based on Evidence Pre-propagation. M.S. Thesis, Intelligent Systems Program, University of Pittsburgh, 2003.

Changhe Yuan, Research and Development of Rough Set Theory-based Data Mining Technology. M.S. Thesis, Computer Science Department, Tongji University, 2001.