Bucket elimination: a unifying framework for reasoning
Artificial Intelligence
Machine Learning
Efficient inference with cardinality-based clique potentials
Proceedings of the 24th international conference on Machine learning
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
MPE and partial inversion in lifted probabilistic variable elimination
AAAI'06 proceedings of the 21st 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
SPOOK: a system for probabilistic object-oriented knowledge representation
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
TildeCRF: conditional random fields for logical sequences
ECML'06 Proceedings of the 17th European conference on Machine Learning
PrDB: managing and exploiting rich correlations in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Lifted aggregation in directed first-order probabilistic models
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Constraint processing in lifted probabilistic inference
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Bisimulation-based approximate lifted inference
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Increasing representational power and scaling reasoning in probabilistic databases
Proceedings of the 13th International Conference on Database Theory
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Speeding up inference in statistical relational learning by clustering similar query literals
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials
The Journal of Machine Learning Research
Learning statistical models from relational data
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Logic, probability and computation: foundations and issues of statistical relational AI
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
Decision-theoretic planning with generalized first-order decision diagrams
Artificial Intelligence
Efficient sequential clamping for lifted message passing
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
Data Mining and Knowledge Discovery
Multi-evidence lifted message passing, with application to PageRank and the Kalman filter
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Lifted relational Kalman filtering
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Lifted probabilistic inference by first-order knowledge compilation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Structured probabilistic inference
International Journal of Approximate Reasoning
JELIA'12 Proceedings of the 13th European conference on Logics in Artificial Intelligence
Combining relational learning with SMT solvers using CEGAR
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
Statistical relational data integration for information extraction
RW'13 Proceedings of the 9th international conference on Reasoning Web: semantic technologies for intelligent data access
Lifted variable elimination: decoupling the operators from the constraint language
Journal of Artificial Intelligence Research
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Lifted inference algorithms exploit repeated structure in probabilistic models to answer queries efficiently. Previous work such as de Salvo Braz et al.'s first-order variable elimination (FOVE) has focused on the sharing of potentials across interchangeable random variables. In this paper, we also exploit interchangeability within individual potentials by introducing counting formulas, which indicate how many of the random variables in a set have each possible value. We present a new lifted inference algorithm, C-FOVE, that not only handles counting formulas in its input, but also creates counting formulas for use in intermediate potentials. C-FOVE can be described succinctly in terms of six operators, along with heuristics for when to apply them. Because counting formulas capture dependencies among large numbers of variables compactly, C-FOVE achieves asymptotic speed improvements compared to FOVE.