pic of me

Arthur Choi


Computer Science Department
University of California, Los Angeles
aychoi(Shift-2)cs.ucla.edu
Born in Atlanta,
I hung out in Ithaca,
Now in Los Angeles.


new: Since Fall 2021, I am now an assistant professor in the Department of Computer Science at Kennesaw State University! new page

I am a member of Adnan Darwiche's Automated Reasoning group. Check out his book!

Interests: Bayesian networks and probabilistic graphical models; learning Bayesian networks; exact and approximate inference; knowledge compilation and tractable models

Relevant to my interests: counting; computability and complexity; explainable artificial intelligence;

What I ate yesterday: poke

Happy watermelon day!

code: pypsdd pysdd sdd



Papers

Arthur Choi and Ruocheng Wang and Adnan Darwiche. On the Relative Expressiveness of Bayesian and Neural Networks. In International Journal of Approximate Reasoning (IJAR), volume 113, pages 303-323, 2019. pdf

Yujia Shen and Haiying Huang and Arthur Choi and Adnan Darwiche. Conditional Independence in Testing Bayesian Networks. In Proceedings of the Thirty-Sixth International Conference on Machine Learning (ICML), pages 5701-5709, 2019. pdf

Andy Shih and Adnan Darwiche and Arthur Choi. Verifying Binarized Neural Networks by Angluin-Style Learning. In Proceedings of the 22nd International Conference on Theory and Applications of Satisfiability Testing (SAT), pages 354-370, 2019. pdf

Andy Shih and Adnan Darwiche and Arthur Choi. Verifying Binarized Neural Networks by Local Automaton Learning (Workshop Version). Presented at the AAAI Spring Symposium on Verification of Neural Networks (VNN), 2019. pdf

Arthur Choi and Weijia Shi and Andy Shih and Adnan Darwiche. Compiling Neural Networks into Tractable Boolean Circuits. Presented at the AAAI Spring Symposium on Verification of Neural Networks (VNN), 2019. pdf

Andy Shih and Arthur Choi and Adnan Darwiche. Compiling Bayesian Networks into Decision Graphs. To appear in Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019. pdf

Yujia Shen and Anchal Goyanka and Adnan Darwiche and Arthur Choi. Structured Bayesian Networks: From Inference to Learning with Routes. To appear in Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019. pdf

Arthur Choi and Adnan Darwiche. On the Relative Expressiveness of Bayesian and Neural Networks. To appear in Proceedings of the 9th International Conference on Probabilistic Graphical Models (PGM), 2018. pdf

Andy Shih and Arthur Choi and Adnan Darwiche. Formal Verification of Bayesian Network Classifiers. To appear in Proceedings of the 9th International Conference on Probabilistic Graphical Models (PGM), 2018. pdf

Andy Shih and Arthur Choi and Adnan Darwiche. A Symbolic Approach to Explaining Bayesian Network Classifiers. To appear in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018. pdf

Yujia Shen and Arthur Choi and Adnan Darwiche. Conditional PSDDs: Modeling and Learning with Modular Knowledge. To appear in Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018. pdf

Eunice Yuh-Jie Chen and Arthur Choi and Adnan Darwiche. On Pruning with the MDL Score. International Journal of Approximate Reasoning (IJAR), 92:363-375, 2018. pdf

Arthur Choi and Yujia Shen and Adnan Darwiche. Tractability in Structured Probability Spaces. In Advances in Neural Information Processing Systems 30 (NIPS), pages 3480-3488, 2017. pdf

Yujia Shen and Arthur Choi and Adnan Darwiche. A Tractable Probabilistic Model for Subset Selection. In Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI), 2017. pdf

Arthur Choi and Adnan Darwiche. On Relaxing Determinism in Arithmetic Circuits. To appear in Proceedings of the Thirty-Fourth International Conference on Machine Learning (ICML), 2017. pdf

Tiansheng Yao and Arthur Choi and Adnan Darwiche. Learning Bayesian Network Parameters under Equivalence Constraints. Artificial Intelligence (AIJ), 244:239-257, 2017. pdf

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 Yuh-Jie 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 Yuh-Jie 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 Yuh-Jie 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 591-599, 2016. pdf

Umut Oztok and Arthur Choi and Adnan Darwiche. Solving PP^PP-Complete 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 2233-2241, 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 2861-2868, 2015. pdf

Eunice Yuh-Jie Chen and Arthur Choi and Adnan Darwiche. Learning Bayesian Networks with Non-Decomposable Scores. In the 4th International Workshop on Graph Structures for Knowledge Representation and Reasoning (GKR), LNAI, pages 50-71, 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 161-170, 2015. pdf

Suming Chen and Arthur Choi and Adnan Darwiche. Computer Adaptive Testing Using the Same-Decision Probability. Presented at the 12th Annual Bayesian Modeling Applications Workshop (BMAW), 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 3503-3510, 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 1565-1573, 2014. pdf

Suming Chen and Arthur Choi and Adnan Darwiche. Algorithms and Applications for the Same-Decision Probability. In Journal of Artificial Intelligence Research (JAIR), Volume 49, pages 601-633, 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 271-292, 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 1502-1510, 2013. pdf

Suming Chen, Arthur Choi and Adnan Darwiche. An Exact Algorithm for Computing the Same-Decision Probability. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), pages 2525-2531, 2013. pdf

Arthur Choi and Adnan Darwiche Dynamic Minimization of Sentential Decision Diagrams. In Proceedings of the 27th Conference on Artificial Intelligence (AAAI), pages 187-194, 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 121-132, 2013. pdf

Suming Chen, Arthur Choi and Adnan Darwiche. The Same-Decision Probability: A New Tool for Decision Making. In Proceedings of the Sixth European Workshop on Probabilistic Graphical Models (PGM), pages 51-58, 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 131-141, 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 705-714, 2012. pdf

Yexiang Xue, Arthur Choi, and Adnan Darwiche. Basing Decisions on Sentences in Decision Diagrams. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI), pages 842-849, 2012. pdf

Arthur Choi, Yexiang Xue, and Adnan Darwiche. Same-Decision Probability: A Confidence Measure for Threshold-Based Decisions. In the International Journal of Approximate Reasoning (IJAR), Vol. 53, No. 9, pages 1415-1428, 2012. 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 39-66, 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 115-124, 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 167-180, 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 65-72, 2010. pdf

Adnan Darwiche and Arthur Choi. Same-Decision Probability: A Confidence Measure for Threshold-Based Decisions under Noisy Sensors. In Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM), pages 113-120, 2010. pdf

Dan He, Arthur Choi, Knot Pipatsrisawat, Adnan Darwiche, Eleazar Eskin. Optimal Algorithms for Haplotype Assembly From Whole-Genome Sequence Data. In Proceedings of the 18th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), pages 183-190, 2010. pdf

Arthur Choi and Adnan Darwiche. Relax then Compensate: On Max-Product Belief Propagation and More. In Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS), pages 351-359, 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



To learn my teachings, I must first teach you how to learn.
The Sphinx
(a metaphor for AI/ML)
The Dark Mark