Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
First order compiler: A deterministic logic program synthesis algorithm
Journal of Symbolic Computation
Fundamentals of speech recognition
Fundamentals of speech recognition
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Recognition of Visual Activities and Interactions by Stochastic Parsing
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Logic to Logic Programming
From Logic to Logic Programming
Parameter Estimation in Stochastic Logic Programs
Machine Learning
Complex Probabilistic Modeling with Recursive Relational Bayesian Networks
Annals of Mathematics and Artificial Intelligence
Learning Probabilistic Models of Relational Structure
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
Efficient EM Learning with Tabulation for Parameterized Logic Programs
CL '00 Proceedings of the First International Conference on Computational Logic
Efficient fixpoint computation in linear tabling
Proceedings of the 5th ACM SIGPLAN international conference on Principles and practice of declaritive programming
ACM SIGKDD Explorations Newsletter
Stochastic attribute-value grammars
Computational Linguistics
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
Estimators for stochastic "Unification-Based" grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
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
Parameter learning of logic programs for symbolic-statistical modeling
Journal of Artificial Intelligence Research
Loglinear models for first-order probabilistic reasoning
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A glimpse of symbolic-statistical modeling by PRISM
Journal of Intelligent Information Systems
New advances in logic-based probabilistic modeling by PRISM
Probabilistic inductive logic programming
| Hi-index | 0.00 |
We introduce negation to a symbolic-statistical modeling language PRISM and propose to eliminate negation by program transformation called negation technique which is applicable to probabilistic logic programs. We also introduce finite PCFGs (probabilistic context free grammars) as PCFGs with finite constraints as part of generative modeling of stochastic HPSGs (head-driven phrase structure grammars). They are a subclass of log-linear models and allow exact computation of normalizing constants. We apply the negation technique to a PDCG (probabilistic definite clause grammar) program written in PRISM that describes a finite PCFG with a height constraint. The resulting program computes a normalizing constant for the finite PCFG in time linear in the given height. We also report on an experiment of parameter learning for a real grammar (ATR grammar) with the height constraint. We have discovered that the height constraint does not necessarily lead to a significant decrease in parsing accuracy.