2024
On Bounding the Behavior of Neurons.
Int. J. Artif. Intell. Tools, May, 2024
On Provenance in Topic Models.
Proceedings of the 2024 ACM Southeast Conference, 2024
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