Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
A view of the EM algorithm that justifies incremental, sparse, and other variants
Learning in graphical models
Constraint Processing
Survey propagation: An algorithm for satisfiability
Random Structures & Algorithms
Disco - Novo - GoGo: integrating local search and complete search with restarts
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Backbones and backdoors in satisfiability
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Solution-guided multi-point constructive search for job shop scheduling
Journal of Artificial Intelligence Research
Backdoors to typical case complexity
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Balance and filtering in structured satisfiable problems
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Heavy-Tailed runtime distributions: heuristics, models and optimal refutations
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
A simple insight into iterative belief propagation's success
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Characterizing propagation methods for boolean satisfiability
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Probabilistically Estimating Backbones and Variable Bias: Experimental Overview
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
VARSAT: Integrating Novel Probabilistic Inference Techniques with DPLL Search
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Evaluating abductive hypotheses using an EM algorithm on BDDs
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Efficient generic search heuristics within the EMBP framework
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Deriving Information from Sampling and Diving
Fundamenta Informaticae - RCRA 2009 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Counting-based search: branching heuristics for constraint satisfaction problems
Journal of Artificial Intelligence Research
On the interpolation between product-based message passing heuristics for SAT
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
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We present a new probabilistic framework for finding likely variable assignments in difficult constraint satisfaction problems. Finding such assignments is key to efficient search, but practical efforts have largely been limited to random guessing and heuristically designed weighting systems. In contrast, we derive a new version of Belief Propagation (BP) using the method of Expectation Maximization (EM). This allows us to differentiate between variables that are strongly biased toward particular values and those that are largely extraneous. Using EM also eliminates the threat of non-convergence associated with regular BP. Theoretically, the derivation exhibits appealing primal/dual semantics. Empirically, it produces an "EMBP"-based heuristic for solving constraint satisfaction problems, as illustrated with respect to the Quasigroup with Holes domain. EMBP outperforms existing techniques for guiding variable and value ordering during backtracking search on this problem.