

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; learning Bayesian networks and related models
Relevant to my interests: counting; logical reasoning and knowledge compilation; computability and complexity; diagnosis and prognosis
What I ate yesterday: empanadas (jamon y queso)
Papers
Yujia Shen and Arthur Choi and Adnan Darwiche. Tractable Operations for Arithmetic Circuits of Probabilistic Models. To appear in Advances in Neural Information Processing Systems 29 (NIPS), 2016. pdf
Eunice YuhJie Chen and Yujia Shen and Arthur Choi and Adnan Darwiche. Learning Bayesian Networks with Ancestral Constraints. To appear in Advances in Neural Information Processing Systems 29 (NIPS), 2016. pdf
Eunice YuhJie Chen and Arthur Choi and Adnan Darwiche. On Pruning with the MDL Score. To appear in Proceedings of the 8th International Conference on Probabilistic Graphical Models (PGM), 2016. pdf
Eunice YuhJie Chen and Arthur Choi and Adnan Darwiche. Enumerating Equivalence Classes of Bayesian Networks using EC Graphs. In Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), pages 591599, 2016. pdf
Umut Oztok and Arthur Choi and Adnan Darwiche. Solving PP^PPComplete Problems Using Knowledge Compilation. To appear in Proceedings of the 15th International Conference on Principles of Knowledge Representation and Reasoning (KR), 2016. pdf
Arthur Choi and Nazgol Tavabi and Adnan Darwiche. Structured Features in Naive Bayes Classification. To appear in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016. pdf
Jessa Bekker and Jesse Davis and Arthur Choi and Adnan Darwiche and Guy Van den Broeck. Tractable Learning for Complex Probability Queries. In Advances in Neural Information Processing Systems 28 (NIPS), pages 22332241, 2015. pdf
Arthur Choi and Guy Van den Broeck and Adnan Darwiche. Tractable Learning for Structured Probability Spaces: A Case Study in Learning Preference Distributions. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI), pages 28612868, 2015. pdf
Eunice YuhJie Chen and Arthur Choi and Adnan Darwiche. Learning Bayesian Networks with NonDecomposable Scores. In the 4th International Workshop on Graph Structures for Knowledge Representation and Reasoning (GKR), LNAI, pages 5071, 2015. pdf
Guy Van den Broeck and Karthika Mohan and Arthur Choi and Adnan Darwiche and Judea Pearl. Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data. In Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI), pages 161170, 2015. pdf
Suming Chen and Arthur Choi and Adnan Darwiche. Computer Adaptive Testing Using the SameDecision Probability. Presented at the 12th Annual Bayesian Modeling Applications Workshop (BMAW), 2015. pdf
Tiansheng Yao and Arthur Choi and Adnan Darwiche. Learning Bayesian Network Parameters under Equivalence Constraints. To appear in Artificial Intelligence (AIJ), 2015. pdf
Arthur Choi and Guy Van den Broeck and Adnan Darwiche. Probability Distributions over Structured Spaces. Presented at the AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches (KRR), 2015. pdf
Suming Chen and Arthur Choi and Adnan Darwiche. Value of Information Based on Decision Robustness. In Proceedings of the 29th Conference on Artificial Intelligence (AAAI), pages 35033510, 2015. pdf
Khaled S. Refaat and Arthur Choi and Adnan Darwiche. Decomposing Parameter Estimation Problems. In Advances in Neural Information Processing Systems 27 (NIPS), pages 15651573, 2014. pdf
Suming Chen and Arthur Choi and Adnan Darwiche. Algorithms and Applications for the SameDecision Probability. In Journal of Artificial Intelligence Research (JAIR), Volume 49, pages 601633, 2014. pdf
Doga Kisa and Guy Van den Broeck and Arthur Choi and Adnan Darwiche. Probabilistic Sentential Decision Diagrams: Learning with Massive Logical Constraints. Presented at the ICML Workshop on Learning Tractable Probabilistic Models (LTPM), 2014. pdf
Doga Kisa and Guy Van den Broeck and Arthur Choi and Adnan Darwiche. Probabilistic Sentential Decision Diagrams. In Proceedings of the 14th International Conference on Principles of Knowledge Representation and Reasoning (KR), 2014. pdf
Johann Schumann, Timmy Mbaya, Ole Mengshoel, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi and Adnan Darwiche. Software Health Management with Bayesian Networks. In Innovations in Systems and Software Engineering, Volume 9, Number 4, pages 271292, 2013. pdf
Khaled S. Refaat, Arthur Choi and Adnan Darwiche. EDML for Learning Parameters in Directed and Undirected Graphical Models. In Advances in Neural Information Processing Systems 26 (NIPS), pages 15021510, 2013. pdf
Suming Chen, Arthur Choi and Adnan Darwiche. An Exact Algorithm for Computing the SameDecision Probability. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), pages 25252531, 2013. pdf
Arthur Choi and Adnan Darwiche Dynamic Minimization of Sentential Decision Diagrams. In Proceedings of the 27th Conference on Artificial Intelligence (AAAI), pages 187194, 2013. pdf
Arthur Choi, Doga Kisa and Adnan Darwiche Compiling Probabilistic Graphical Models using Sentential Decision Diagrams. In Proceedings of the 12th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU), pages 121132, 2013. pdf
Suming Chen, Arthur Choi and Adnan Darwiche. The SameDecision Probability: A New Tool for Decision Making. In Proceedings of the Sixth European Workshop on Probabilistic Graphical Models (PGM), pages 5158, 2012. pdf
Guy Van den Broeck, Arthur Choi and Adnan Darwiche. Lifted Relax, Compensate and then Recover: From Approximate to Exact Lifted Probabilistic Inference. In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI), pages 131141, 2012. pdf
Khaled S. Refaat, Arthur Choi and Adnan Darwiche. New Advances and Theoretical Insights into EDML. In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI), pages 705714, 2012. pdf
Yexiang Xue, Arthur Choi, and Adnan Darwiche. Basing Decisions on Sentences in Decision Diagrams. In Proceedings of the TwentySixth AAAI Conference on Artificial Intelligence (AAAI), pages 842849, 2012. pdf
Arthur Choi, Yexiang Xue, and Adnan Darwiche. SameDecision Probability: A Confidence Measure for ThresholdBased Decisions. In the International Journal of Approximate Reasoning (IJAR), Vol. 53, No. 9, 2012, pages 14151428. pdf
Arthur Choi, Lu Zheng, Adnan Darwiche, Ole J. Mengshoel. A Tutorial on Bayesian Networks for System Health Management. In Machine Learning and Knowledge Discovery for Engineering Systems Health Management, Chapter 2, pages 3966, 2012. pdf
Arthur Choi, Khaled S. Refaat and Adnan Darwiche. EDML: A Method for Learning Parameters in Bayesian Networks. In Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence (UAI), pages 115124, 2011. pdf
Arthur Choi and Adnan Darwiche. Relax, Compensate and then Recover. In New Frontiers in Artificial Intelligence, volume 6797 of Lecture Notes in Computer Science, pages 167180, 2011. pdf
Arthur Choi and Adnan Darwiche. On a Discrete Dirichlet Model. In Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM), pages 6572, 2010. pdf
Adnan Darwiche and Arthur Choi. SameDecision Probability: A Confidence Measure for ThresholdBased Decisions under Noisy Sensors. In Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM), pages 113120, 2010. pdf
Dan He, Arthur Choi, Knot Pipatsrisawat, Adnan Darwiche, Eleazar Eskin. Optimal Algorithms for Haplotype Assembly From WholeGenome Sequence Data. In Proceedings of the 18th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), pages 183190, 2010. pdf
Arthur Choi and Adnan Darwiche. Relax then Compensate: On MaxProduct Belief Propagation and More. In Proceedings of the TwentyThird Annual Conference on Neural Information Processing Systems (NIPS), pages 351359, 2009. pdf
Arthur Choi, Trevor Standley and Adnan Darwiche. Approximating Weighted MaxSAT Problems by Compensating for Relaxations. In Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming (CP), pages 211225, 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 135147, 2008. pdf
Knot Pipatsrisawat, Akop Palyan, Mark Chavira, Arthur Choi, and Adnan Darwiche. Solving Weighted MaxSAT Problems in a Reduced Search Space: A Performance Analysis. In Journal on Satisfiability, Boolean Modeling and Computation (JSAT), pages 191217, 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 7987, 2008. pdf
Arthur Choi and Adnan Darwiche. Focusing Generalizations of Belief Propagation on Targeted Queries. In Proceedings of the TwentyThird AAAI Conference on Artificial Intelligence (AAAI), pages 10241030, 2008. pdf
Arthur Choi and Adnan Darwiche. ManyPairs Mutual Information for Adding Structure to Belief Propagation Approximations. In Proceedings of the TwentyThird AAAI Conference on Artificial Intelligence (AAAI), pages 10311036, 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 5766, 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 8089, 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 11071114, 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 128135, 2005. pdf bib
