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Arthur ChoiComputer Science Department University of California, Los Angeles aychoi(Shift-2)cs.ucla.edu |
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Born in Atlanta, I hung out in Ithaca, Now in Los Angeles. |
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I am a member of Adnan Darwiche's Automated Reasoning group. Check out his new book!
Interests: Bayesian networks and probabilistic graphical models; exact and approximate inference, particularly iterative belief propagation and related methods;
Relevant to my interests: counting; diagnosis and prognosis; logical reasoning; computability and complexity; computational biology
What I ate yesterday: nong shim seafood ramyun
Papers
Arthur Choi and Adnan Darwiche. Relax then Compensate: On Max-Product Belief Propagation and More. To appear in Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS), 2009. pdf
Arthur Choi, Trevor Standley and Adnan Darwiche. Approximating Weighted Max-SAT Problems by Compensating for Relaxations. In Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming (CP), pages 211-225, 2009. pdf
Arthur Choi, Noah Zaitlen, Buhm Hahn, Knot Pipatsrisawat, Adnan Darwiche, and Eleazar Eskin. Efficient Genome Wide Tagging by Reduction to SAT. In Proceedings of the 8th Workshop on Algorithms in Bioinformatics (WABI), pages 135-147, 2008. pdf
Knot Pipatsrisawat, Akop Palyan, Mark Chavira, Arthur Choi, and Adnan Darwiche. Solving Weighted Max-SAT Problems in a Reduced Search Space: A Performance Analysis. In Journal on Satisfiability, Boolean Modeling and Computation (JSAT), pages 191-217, 2008. pdf
Arthur Choi and Adnan Darwiche. Approximating the Partition Function by Deleting and then Correcting for Model Edges. In Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI), pages 79-87, 2008. pdf
Arthur Choi and Adnan Darwiche. Focusing Generalizations of Belief Propagation on Targeted Queries. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI), pages 1024-1030, 2008. pdf
Arthur Choi and Adnan Darwiche. Many-Pairs Mutual Information for Adding Structure to Belief Propagation Approximations. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI), pages 1031-1036, 2008. pdf
Arthur Choi and Adnan Darwiche. Approximating the Partition Function by Deleting and then Correcting for Model Edges (Extended Abstract). Presented at NIPS Workshop on Approximate Bayesian Inference in Continuous/Hybrid Systems, 2007. pdf
Arthur Choi, Mark Chavira and Adnan Darwiche. Node Splitting: A Scheme for Generating Upper Bounds in Bayesian Networks. In Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence (UAI), pages 57-66, 2007. pdf
Arthur Choi and Adnan Darwiche. A Variational Approach for Approximating Bayesian Networks by Edge Deletion. In Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence (UAI), pages 80-89, 2006. pdf bib talk
Arthur Choi and Adnan Darwiche. An Edge Deletion Semantics for Belief Propagation and its Practical Impact on Approximation Quality. In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI), pages 1107-1114, 2006. pdf bib talk
Arthur Choi, Hei Chan, and Adnan Darwiche. On Bayesian Network Approximation by Edge Deletion. In Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence (UAI), pages 128-135, 2005. pdf bib
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