Probabilistic Languages: A Review and Some Open Questions
ACM Computing Surveys (CSUR)
Defense of the ansatz for dynamical hierarchies
Artificial Life
Stochastic k-testable Tree Languages and Applications
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Estimation of probabilistic context-free grammars
Computational Linguistics
Statistical properties of probabilistic context-free grammars
Computational Linguistics
Conditions on consistency of probabilistic Tree Adjoining Grammars
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Probabilistic Finite-State Machines-Part II
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parsing with Probabilistic Strictly Locally Testable Tree Languages
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic parsing strategies
Journal of the ACM (JACM)
Probabilistic parsing strategies
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
An alternative method of training probabilistic LR parsers
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Estimation of consistent probabilistic context-free grammars
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Probabilistic Context-Free Grammars Estimated from Infinite Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting Grammars from RNA Sequences
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Maximum likelihood analysis of algorithms and data structures
Theoretical Computer Science
Estimation of stochastic context-free grammars and their use as language models
Computer Speech and Language
A bibliographical study of grammatical inference
Pattern Recognition
Smoothing and compression with stochastic k-testable tree languages
Pattern Recognition
Computation of infix probabilities for probabilistic context-free grammars
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A new general grammar formalism for parsing
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Consistency of stochastic context-free grammars
Mathematical and Computer Modelling: An International Journal
Stochastic context-free grammars, regular languages, and newton's method
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
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An important problem related to the probabilistic estimation of Stochastic Context-Free Grammars (SCFGs) is guaranteeing the consistency of the estimated model. This problem was considered in [3], [14] and studied in [10], [4] for unambiguous SCFGs only, when the probabilistic distributions were estimated by the relative frequencies in a training sample. In this work, we extend this result by proving that the property of consistency is guaranteed for all SCFGs without restrictions, when the probability distributions are learned from the classical Inside-Outside and Viterbi algorithms, both of which are based on Growth Transformations. Other important probabilistic properties which are related to these results are also proven.