Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Introduction to algorithms
Fundamentals of speech recognition
Fundamentals of speech recognition
Probabilistic logic programming
Information and Computation
Artificial Intelligence - Special volume on natural language processing
Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Probabilistic deductive databases
ILPS '94 Proceedings of the 1994 International Symposium on Logic programming
Answering queries from context-sensitive probabilistic knowledge bases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Probabilistic Languages: A Review and Some Open Questions
ACM Computing Surveys (CSUR)
From Logic to Logic Programming
From Logic to Logic Programming
Parameter Estimation in Stochastic Logic Programs
Machine Learning
Expert Systems and Probabiistic Network Models
Expert Systems and Probabiistic Network Models
OLD Resolution with Tabulation
Proceedings of the Third International Conference on Logic Programming
Parameterized Logic Programs where Computing Meets Learning
FLOPS '01 Proceedings of the 5th International Symposium on Functional and Logic Programming
Efficient EM Learning with Tabulation for Parameterized Logic Programs
CL '00 Proceedings of the First International Conference on Computational Logic
Learning probabilities for noisy first-order rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
PRISM: a language for symbolic-statistical modeling
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Prediction is deduction but explanation is abduction
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
IBAL: a probabilistic rational programming language
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Effective Bayesian inference for stochastic programs
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Loglinear models for first-order probabilistic reasoning
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Parameterized Logic Programs where Computing Meets Learning
FLOPS '01 Proceedings of the 5th International Symposium on Functional and Logic Programming
A Machine Learning Approach to Test Data Generation: A Case Study in Evaluation of Gene Finders
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Logic-Based Probabilistic Modeling
WoLLIC '09 Proceedings of the 16th International Workshop on Logic, Language, Information and Computation
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Preprocessing for Optimization of Probabilistic-Logic Models for Sequence Analysis
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Chr(prism)-based probabilistic logic learning
Theory and Practice of Logic Programming
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We propose statistical abduction as a first-order logical framework for representing, inferring and learning probabilistic knowledge. It semantically integrates logical abduction with a parameterized distribution over abducibles. We show that statistical abduction combined with tabulated search provides an efficient algorithm for probability computation, a Viterbi-like algorithm for finding the most likely explanation, and an EM learning algorithm (the graphical EM algorithm) for learning parameters associated with the distribution which achieve the same computational complexity as those specialized algorithms for HMMs (hidden Markov models), PCFGs (probabilistic context-free grammars) and sc-BNs (singly connected Bayesian networks).