Arthur Choi

According to our database1, Arthur Choi authored at least 60 papers between 2005 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
On Training Neurons with Bounded Compilations.
Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning, 2023

On Bounding the Behavior of a Neuron.
Proceedings of the Thirty-Sixth International Florida Artificial Intelligence Research Society Conference, 2023

2020
On Symbolically Encoding the Behavior of Random Forests.
CoRR, 2020

A New Perspective on Learning Context-Specific Independence.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Supervised Learning with Background Knowledge.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

On Tractable Representations of Binary Neural Networks.
Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, 2020

2019
On the relative expressiveness of Bayesian and neural networks.
Int. J. Approx. Reason., 2019

Verifying Binarized Neural Networks by Angluin-Style Learning.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2019, 2019

Conditional Independence in Testing Bayesian Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Compiling Bayesian Network Classifiers into Decision Graphs.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Structured Bayesian Networks: From Inference to Learning with Routes.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
On pruning with the MDL Score.
Int. J. Approx. Reason., 2018

Formal Verification of Bayesian Network Classifiers.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

On the Relative Expressiveness of Bayesian and Neural Networks.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

A Symbolic Approach to Explaining Bayesian Network Classifiers.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Conditional PSDDs: Modeling and Learning With Modular Knowledge.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Learning Bayesian network parameters under equivalence constraints.
Artif. Intell., 2017

A Tractable Probabilistic Model for Subset Selection.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Tractability in Structured Probability Spaces.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

On Relaxing Determinism in Arithmetic Circuits.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Tractable Operations for Arithmetic Circuits of Probabilistic Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning Bayesian networks with ancestral constraints.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Solving PP<sup>PP</sup>-Complete Problems Using Knowledge Compilation.
Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Fifteenth International Conference, 2016

Enumerating Equivalence Classes of Bayesian Networks using EC Graphs.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Structured Features in Naive Bayes Classification.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Dual Decomposition from the Perspective of Relax, Compensate and then Recover.
CoRR, 2015

Computer Adaptive Testing Using the Same-Decision Probability.
Proceedings of the Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015) co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), 2015

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Tractable Learning for Complex Probability Queries.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Tractable Learning for Structured Probability Spaces: A Case Study in Learning Preference Distributions.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Learning Bayesian Networks with Non-Decomposable Scores.
Proceedings of the Graph Structures for Knowledge Representation and Reasoning, 2015

Probability Distributions over Structured Spaces.
Proceedings of the 2015 AAAI Spring Symposia, 2015

Value of Information Based on Decision Robustness.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Algorithms and Applications for the Same-Decision Probability.
J. Artif. Intell. Res., 2014

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data.
CoRR, 2014

Decomposing Parameter Estimation Problems.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Probabilistic Sentential Decision Diagrams.
Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Fourteenth International Conference, 2014

2013
Software health management with Bayesian networks.
Innov. Syst. Softw. Eng., 2013

EDML for Learning Parameters in Directed and Undirected Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

An Exact Algorithm for Computing the Same-Decision Probability.
Proceedings of the IJCAI 2013, 2013

Compiling Probabilistic Graphical Models Using Sentential Decision Diagrams.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2013

Dynamic Minimization of Sentential Decision Diagrams.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
Same-decision probability: A confidence measure for threshold-based decisions.
Int. J. Approx. Reason., 2012

New Advances and Theoretical Insights into EDML.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Lifted Relax, Compensate and then Recover: From Approximate to Exact Lifted Probabilistic Inference.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Basing Decisions on Sentences in Decision Diagrams.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
EDML: A Method for Learning Parameters in Bayesian Networks.
Proceedings of the UAI 2011, 2011

2010
Optimal algorithms for haplotype assembly from whole-genome sequence data.
Bioinform., 2010

Relax, Compensate and Then Recover.
Proceedings of the New Frontiers in Artificial Intelligence, 2010

2009
Approximating MAP by Compensating for Structural Relaxations.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Approximating Weighted Max-SAT Problems by Compensating for Relaxations.
Proceedings of the Principles and Practice of Constraint Programming, 2009

2008
Solving Weighted Max-SAT Problems in a Reduced Search Space: A Performance Analysis.
J. Satisf. Boolean Model. Comput., 2008

Efficient Genome Wide Tagging by Reduction to SAT.
Proceedings of the Algorithms in Bioinformatics, 8th International Workshop, 2008

Approximating the Partition Function by Deleting and then Correcting for Model Edges.
Proceedings of the UAI 2008, 2008

Many-Pairs Mutual Information for Adding Structure to Belief Propagation Approximations.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

Focusing Generalizations of Belief Propagation on Targeted Queries.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Node Splitting: A Scheme for Generating Upper Bounds in Bayesian Networks.
Proceedings of the UAI 2007, 2007

2006
A Variational Approach for Approximating Bayesian Networks by Edge Deletion.
Proceedings of the UAI '06, 2006

An Edge Deletion Semantics for Belief Propagation and its Practical Impact on Approximation Quality.
Proceedings of the Proceedings, 2006

2005
On Bayesian Network Approximation by Edge Deletion.
Proceedings of the UAI '05, 2005


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