Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Efficient clustering of high-dimensional data sets with application to reference matching
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Automating first-order relational logic
SIGSOFT '00/FSE-8 Proceedings of the 8th ACM SIGSOFT international symposium on Foundations of software engineering: twenty-first century applications
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Using weighted MAX-SAT engines to solve MPE
Eighteenth national conference on Artificial intelligence
Adaptive duplicate detection using learnable string similarity measures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Machine Learning
Discriminative training of Markov logic networks
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
First-order probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Lifted first-order probabilistic inference
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Discriminative Structure Learning of Markov Logic Networks
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
A Generalized Joint Inference Approach for Citation Matching
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Just Add Weights: Markov Logic for the Semantic Web
Uncertainty Reasoning for the Semantic Web I
Unifying logical and statistical AI
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Scaling textual inference to the web
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Integrating multiple learning components through Markov logic
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
A general method for reducing the complexity of relational inference and its application to MCMC
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Lifted first-order belief propagation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Probabilistic inductive logic programming
An architecture for adaptive algorithmic hybrids
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Machine reading at the University of Washington
FAM-LbR '10 Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading
Speeding up inference in statistical relational learning by clustering similar query literals
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Discovery of logic relations for text mining adaptation using unlabeled data
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Generative Structure Learning for Markov Logic Networks
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
Tuffy: scaling up statistical inference in Markov logic networks using an RDBMS
Proceedings of the VLDB Endowment
Web information extraction using markov logic networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Pruning search space for weighted first order horn clause satisfiability
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Database foundations for scalable RDF processing
RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
A declarative approach to automated configuration
lisa'12 Proceedings of the 26th international conference on Large Installation System Administration: strategies, tools, and techniques
Programming with personalized pagerank: a locally groundable first-order probabilistic logic
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Combining relational learning with SMT solvers using CEGAR
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
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Propositionalization of a first-order theory followed by satisfiability testing has proved to be a remarkably efficient approach to inference in relational domains such as planning (Kautz & Selman 1996) and verification (Jackson 2000). More recently, weighted satisfiability solvers have been used successfully for MPE inference in statistical relational learners (Singla & Domingos 2005). However, fully instantiating a finite first-order theory requires memory on the order of the number of constants raised to the arity of the clauses, which significantly limits the size of domains it can be applied to. In this paper we propose LazySAT, a variation of the Walk-SAT solver that avoids this blowup by taking advantage of the extreme sparseness that is typical of relational domains (i.e., only a small fraction of ground atoms are true, and most clauses are trivially satisfied). Experiments on entity resolution and planning problems show that LazySAT reduces memory usage by orders of magnitude compared to Walk-SAT, while taking comparable time to run and producing the same solutions.