publications

2020

  1. Lifted Generalized Belief Propagation: Relax, Compensate & Recover
    Guy Van den Broeck and Arthur Choi and Adnan Darwiche
    In An Introduction to Lifted Probabilistic Inference 2020
  2. On Tractable Representations of Binary Neural Networks
    Weijia Shi and Andy Shih and Adnan Darwiche and and Arthur Choi
    In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR) 2020
  3. A New Perspective on Learning Context-Specific Independence
    Yujia Shen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM) 2020
  4. Supervised Learning with Background Knowledge
    Yizuo Chen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM) 2020
  5. Supervised Learning with Background Knowledge
    Yizuo Chen and Arthur Choi and Adnan Darwiche
    In 1st Workshop on Foundations of Trustworthy AI — Integrating Learning, Optimization and Reasoning (TAILOR) 2020
  6. On Symbolically Encoding the Behavior of Random Forests
    Arthur Choi and Andy Shih and Anchal Goyanka and Adnan Darwiche
    In 3rd Workshop on Formal Methods for ML-Enabled Autonomous Systems (FoMLAS) 2020

2019

  1. On the Relative Expressiveness of Bayesian and Neural Networks
    Arthur Choi and Ruocheng Wang and Adnan Darwiche
    International Journal of Approximate Reasoning (IJAR) 2019
  2. Verifying Binarized Neural Networks by Angluin-Style Learning
    Andy Shih and Adnan Darwiche and and Arthur Choi
    In Proceedings of the 22nd International Conference on Theory and Applications of Satisfiability Testing (SAT) 2019
  3. Conditional Independence in Testing Bayesian Networks
    Yujia Shen and Haiying Huang and Arthur Choi and Adnan Darwiche
    In Proceedings of the Thirty-Sixth International Conference on Machine Learning (ICML) 2019
  4. Compiling Bayesian Networks into Decision Graphs
    Andy Shih and Arthur Choi and Adnan Darwiche
    In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI) 2019
  5. Structured Bayesian Networks: From Inference to Learning with Routes
    Yujia Shen and Anchal Goyanka and Adnan Darwiche and and Arthur Choi
    In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI) 2019
  6. Verifying Binarized Neural Networks by Local Automaton Learning
    Andy Shih and Adnan Darwiche and and Arthur Choi
    In AAAI Spring Symposium on Verification of Neural Networks (VNN) 2019
  7. Compiling Neural Networks into Tractable Boolean Circuits
    Arthur Choi and Weijia Shi and Andy Shih and Adnan Darwiche
    In AAAI Spring Symposium on Verification of Neural Networks (VNN) 2019

2018

  1. On Pruning with the MDL Score
    Eunice Yuh-Jie Chen and Adnan Darwiche and and Arthur Choi
    International Journal of Approximate Reasoning (IJAR) 2018
  2. On the Relative Expressiveness of Bayesian and Neural Networks
    Arthur Choi and Adnan Darwiche
    In Proceedings of the 9th International Conference on Probabilistic Graphical Models (PGM) 2018
  3. Formal Verification of Bayesian Network Classifiers
    Andy Shih and Arthur Choi and Adnan Darwiche
    In Proceedings of the 9th International Conference on Probabilistic Graphical Models (PGM) 2018
  4. A Symbolic Approach to Explaining Bayesian Network Classifiers
    Andy Shih and Arthur Choi and Adnan Darwiche
    In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI) 2018
  5. Conditional PSDDs: Modeling and Learning with Modular Knowledge
    Yujia Shen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI) 2018
  6. Explaining the Decisions of a Route Classifier
    Weijia Shi and Adnan Darwiche and and Arthur Choi
    In 13th Women in Machine Learning Workshop (WiML) 2018
  7. Integrating Grammars with Logic
    Ingrid Mattinger and Adnan Darwiche and and Arthur Choi
    In 13th Women in Machine Learning Workshop (WiML) 2018

2017

  1. Learning Bayesian Network Parameters under Equivalence Constraints
    Tiansheng Yao and Arthur Choi and Adnan Darwiche
    Artificial Intelligence 2017
  2. Tractability in Structured Probability Spaces
    Arthur Choi and Yujia Shen and Adnan Darwiche
    In Advances in Neural Information Processing Systems 30 (NIPS) 2017
  3. A Tractable Probabilistic Model for Subset Selection
    Yujia Shen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI) 2017
  4. On Relaxing Determinism in Arithmetic Circuits
    Arthur Choi and Adnan Darwiche
    In Proceedings of the Thirty-Fourth International Conference on Machine Learning (ICML) 2017

2016

  1. Learning Bayesian Networks with Ancestral Constraints
    Eunice Yuh-Jie Chen and Yujia Shen and Arthur Choi and Adnan Darwiche
    In Advances in Neural Information Processing Systems 29 (NIPS) 2016
  2. Tractable Operations for Arithmetic Circuits of Probabilistic Models
    Yujia Shen and Arthur Choi and Adnan Darwiche
    In Advances in Neural Information Processing Systems 29 (NIPS) 2016
  3. On Pruning with the MDL Score
    Eunice Yuh-Jie Chen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 8th International Conference on Probabilistic Graphical Models (PGM) 2016
  4. Enumerating Equivalence Classes of Bayesian Networks using EC Graphs
    Eunice Yuh-Jie Chen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS) 2016
  5. Solving PP^PP-Complete Problems Using Knowledge Compilation
    Umut Oztok and Arthur Choi and Adnan Darwiche
    In Proceedings of the 15th International Conference on Principles of Knowledge Representation and Reasoning (KR) 2016
  6. Structured Features in Naive Bayes Classification
    Arthur Choi and Nazgol Tavabi and Adnan Darwiche
    In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI) 2016
  7. Learning the Structure of Probabilistic SDDs
    Jessa Bekker and Arthur Choi and Guy Van den Broeck
    In 11th Women in Machine Learning Workshop (WiML) 2016
  8. Same Decision Probability in Neurocritical Care
    Fabien Scalzo and Arthur Choi and Adnan Darwiche
    In Machine Learning in Health Care 2016

2015

  1. Learning Bayesian Network Parameters under Equivalence Constraints
    Tiansheng Yao and Arthur Choi and Adnan Darwiche
    Artificial Intelligence 2015
  2. Learning Bayesian Networks with Non-Decomposable Scores
    Eunice Yuh-Jie Chen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 4th International Workshop on Graph Structures for Knowledge Representation and Reasoning (GKR’15) 2015
  3. Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
    Guy Van den Broeck and Karthika Mohan and Arthur Choi and Adnan Darwiche and Judea Pearl
    In Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI) 2015
  4. Tractable Learning for Complex Probability Queries
    Jessa Bekker and Jesse Davis and Arthur Choi and Adnan Darwiche and Guy Van den Broeck
    In Advances in Neural Information Processing Systems 28 (NIPS) 2015
  5. Value of Information Based on Decision Robustness
    Suming Chen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 29th Conference on Artificial Intelligence (AAAI) 2015
  6. Tractable Learning for Structured Probability Spaces: A Case Study in Learning Preference Distributions
    Arthur Choi and Guy Van den Broeck and Adnan Darwiche
    In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI) 2015
  7. Computer Adaptive Testing Using the Same-Decision Probability
    Suming Chen and Arthur Choi and Adnan Darwiche
    In 12th Annual Bayesian Modeling Applications Workshop (BMAW) 2015
  8. Probability Distributions over Structured Spaces
    Arthur Choi and Guy Van den Broeck and Adnan Darwiche
    In AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches (KRR) 2015
  9. Different Strokes: Causality and Outcomes in the NINDS-tPA Trials
    David S. Liebeskind and Arthur Choi and Nerses Sanossian and Scot Fang and Adnan Darwiche and Fabien Scalzo
    Stroke 2015

2014

  1. Algorithms and Applications for the Same-Decision Probability
    Suming Chen and Arthur Choi and Adnan Darwiche
    Journal of Artificial Intelligence Research (JAIR) 2014
  2. Probabilistic Sentential Decision Diagrams
    Doga Kisa and Guy Van den Broeck and Arthur Choi and Adnan Darwiche
    In Proceedings of the 14th International Conference on Principles of Knowledge Representation and Reasoning (KR) 2014
  3. Decomposing Parameter Estimation Problems
    Khaled S. Refaat and Arthur Choi and Adnan Darwiche
    In Advances in Neural Information Processing Systems 27 (NIPS) 2014
  4. Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
    Guy Van den Broeck and Karthika Mohan and Arthur Choi and Judea Pearl
    In ICML Workshop on Causal Modeling & Machine Learning 2014
  5. Probabilistic Sentential Decision Diagrams: Learning with Massive Logical Constraints
    Doga Kisa and Guy Van den Broeck and Arthur Choi and Adnan Darwiche
    In ICML Workshop on Learning Tractable Probabilistic Models (LTPM) 2014

2013

  1. Software Health Management with Bayesian Networks
    Johann Schumann and Timmy Mbaya and Ole Mengshoel and Knot Pipatsrisawat and Ashok Srivastava and Arthur Choi and Adnan Darwiche
    Innovations in Systems and Software Engineering 2013
  2. EDML for Learning Parameters in Directed and Undirected Graphical Models
    Khaled S. Refaat and Arthur Choi and Adnan Darwiche
    In Advances in Neural Information Processing Systems 26 (NIPS) 2013
  3. An Exact Algorithm for Computing the Same-Decision Probability
    Suming Chen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI) 2013
  4. Dynamic Minimization of Sentential Decision Diagrams
    Arthur Choi and Adnan Darwiche
    In Proceedings of the 27th Conference on Artificial Intelligence (AAAI) 2013
  5. Compiling Probabilistic Graphical Models using Sentential Decision Diagrams
    Arthur Choi and Doga Kisa and Adnan Darwiche
    In Proceedings of the 12th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU) 2013
  6. EDML for Learning Parameters in Directed and Undirected Graphical Models
    Khaled S. Refaat and Arthur Choi and Adnan Darwiche
    In ICML 2013 Workshop on Inferning: Interactions between Inference and Learning 2013
  7. Learning Bayesian Networks under Equivalence Constraints (Abstract)
    Tiansheng Yao and Arthur Choi and Adnan Darwiche
    In Second Workshop on Combining Constraint Solving with Mining and Learning (CoCoMiLe) 2013

2012

  1. Same-Decision Probability: A Confidence Measure for Threshold-Based Decisions
    Arthur Choi and Yexiang Xue and Adnan Darwiche
    International Journal of Approximate Reasoning (IJAR) 2012
  2. A Tutorial on Bayesian Networks for System Health Management
    Arthur Choi and Lu Zheng and Adnan Darwiche and Ole J. Mengshoel
    In Machine Learning and Knowledge Discovery for Engineering Systems Health Management 2012
  3. Basing Decisions on Sentences in Decision Diagrams
    Yexiang Xue and Arthur Choi and Adnan Darwiche
    In Proceedings of the 26th Conference on Artificial Intelligence (AAAI) 2012
  4. Lifted Relax, Compensate and then Recover: From Approximate to Exact Lifted Probabilistic Inference
    Guy Van den Broeck and Arthur Choi and Adnan Darwiche
    In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI) 2012
  5. New Advances and Theoretical Insights into EDML
    Khaled S. Refaat and Arthur Choi and Adnan Darwiche
    In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI) 2012
  6. The Same-Decision Probability: A New Tool for Decision Making
    Suming Chen and Arthur Choi and Adnan Darwiche
    In Proceedings of the 6th European Workshop on Probabilistic Graphical Models (PGM) 2012
  7. Concept Networks (Abstract)
    Tiansheng Yao and Arthur Choi and Adnan Darwiche
    In The Uncertainty in Natural Intelligence Workshop at UAI 2012

2011

  1. Relax, Compensate and Then Recover
    Arthur Choi and Adnan Darwiche
    In New Frontiers in Artificial Intelligence 2011
  2. EDML: A Method for Learning Parameters in Bayesian Networks
    Arthur Choi and Khaled S. Refaat and Adnan Darwiche
    In Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence (UAI) 2011

2010

  1. Optimal Algorithms for Haplotype Assembly from Whole-Genome Sequence Data
    Dan He and Arthur Choi and Knot Pipatsrisawat and Adnan Darwiche and Eleazar Eskin
    Bioinformatics [ISMB] 2010
  2. Optimal Algorithms for Haplotype Assembly From Whole-Genome Sequence Data
    Dan He and Arthur Choi and Knot Pipatsrisawat and Adnan Darwiche and Eleazar Eskin
    In Proceedings of the 18th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) 2010
  3. Same-Decision Probability: A Confidence Measure for Threshold-Based Decisions under Noisy Sensors
    Adnan Darwiche and and Arthur Choi
    In Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM) 2010
  4. On a Discrete Dirichlet Model
    Arthur Choi and Adnan Darwiche
    In Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM) 2010

2009

  1. An Edge Deletion Semantics for Belief Propagation
    Arthur Choi and Adnan Darwiche
    In 2009
  2. Approximating Weighted Max-SAT Problems by Compensating for Relaxations
    Arthur Choi and Trevor Standley and Adnan Darwiche
    In Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming (CP) 2009
  3. Relax then Compensate: On Max-Product Belief Propagation and More
    Arthur Choi and Adnan Darwiche
    In Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS) 2009

2008

  1. Solving Weighted Max-SAT Problems in a Reduced Search Space: A Performance Analysis
    Knot Pipatsrisawat and Akop Palyan and Mark Chavira and Arthur Choi and Adnan Darwiche
    Journal on Satisfiability Boolean Modeling and Computation (JSAT) 2008
  2. Many-Pairs Mutual Information for Adding Structure to Belief Propagation Approximations
    Arthur Choi and Adnan Darwiche
    In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI) 2008
  3. Focusing Generalizations of Belief Propagation on Targeted Queries
    Arthur Choi and Adnan Darwiche
    In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI) 2008
  4. Approximating the Partition Function by Deleting and then Correcting for Model Edges
    Arthur Choi and Adnan Darwiche
    In Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI) 2008
  5. Efficient Genome Wide Tagging by Reduction to SAT
    Arthur Choi and Noah Zaitlen and Buhm Hahn and Knot Pipatsrisawat and Adnan Darwiche and Eleazar Eskin
    In Proceedings of the 8th Workshop on Algorithms in Bioinformatics (WABI) 2008
  6. Approximating the Partition Function by Deleting and then Correcting for Model Edges
    Arthur Choi and Adnan Darwiche
    In Information Theory and Applications Workshop 2008

2007

  1. Node Splitting: A Scheme for Generating Upper Bounds in Bayesian Networks
    Arthur Choi and Mark Chavira and Adnan Darwiche
    In Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence (UAI) 2007
  2. Approximating the Partition Function by Deleting and then Correcting for Model Edges
    Arthur Choi and Adnan Darwiche
    In NIPS Workshop on Approximate Bayesian Inference in Continuous/Hybrid Systems 2007
  3. A New Semantics for Belief Propagation: Theoretical and Practical Implications
    Arthur Choi and Adnan Darwiche
    In Information Theory and Applications Workshop 2007

2006

  1. An Edge Deletion Semantics for Belief Propagation and its Practical Impact on Approximation Quality
    Arthur Choi and Adnan Darwiche
    In Proceedings of the 21st AAAI Conference on Artificial Intelligence (AAAI) 2006
  2. A Variational Approach for Approximating Bayesian Networks by Edge Deletion
    Arthur Choi and Adnan Darwiche
    In Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence (UAI) 2006

2005

  1. On Bayesian Network Approximation by Edge Deletion
    Arthur Choi and Hei Chan and Adnan Darwiche
    In Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence (UAI) 2005