Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Zero-suppressed BDDs for set manipulation in combinatorial problems
DAC '93 Proceedings of the 30th international Design Automation Conference
A Linear-Time Algorithm for Finding Tree-Decompositions of Small Treewidth
SIAM Journal on Computing
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence - special issue on computational tradeoffs under bounded resources
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Hierarchical Representations of Discrete Functions, with Application to Model Checking
CAV '94 Proceedings of the 6th International Conference on Computer Aided Verification
A differential approach to inference in Bayesian networks
Journal of the ACM (JACM)
Algorithms and Complexity Results for #SAT and Bayesian Inference
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Probabilistic decision graphs-combining verification and AI techniques for probabilistic inference
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - New trends in probabilistic graphical models
Parameter estimation for probabilistic finite-state transducers
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
New developments in parsing technology
Stochastic simulation algorithms for dynamic probabilistic networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
New advances in inference by recursive conditioning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Value elimination: bayesian inference via backtracking search
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Monolingual probabilistic programming using generalized coroutines
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Training a log-linear parser with loss functions via softmax-margin
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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We introduce a probabilistic formalism handling both Markov random fields of bounded tree width and probabilistic context-free grammars. Our models are based on case-factor diagrams (CFDs) which are similar to binary decision diagrams (BDDs) but are more concise for circuits of bounded tree width. A probabilistic model consists of a CFD defining a feasible set of Boolean assignments and a weight (or cost) for each individual Boolean variable. We give versions of the inside-outside algorithm and the Viterbi algorithm for these models.