Information Processing Letters
Inferring decision trees using the minimum description length principle
Information and Computation
Inductive inference from positive data is powerful
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Machine Learning
Efficient learning of context-free grammars from positive structural examples
Information and Computation
Natural language parsing as statistical pattern recognition
Natural language parsing as statistical pattern recognition
Bayesian learning of probabilistic language models
Bayesian learning of probabilistic language models
Building probabilistic models for natural language
Building probabilistic models for natural language
An introduction to Kolmogorov complexity and its applications (2nd ed.)
An introduction to Kolmogorov complexity and its applications (2nd ed.)
Inference of Reversible Languages
Journal of the ACM (JACM)
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
Inducing Probabilistic Grammars by Bayesian Model Merging
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Unsupervised language acquisition
Unsupervised language acquisition
Stochastic attribute-value grammars
Computational Linguistics
Towards history-based grammars: using richer models for probabilistic parsing
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Relating complexity to practical performance in parsing with wide-coverage unification grammars
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
A new statistical parser based on bigram lexical dependencies
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Inside-outside reestimation from partially bracketed corpora
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Estimation of stochastic attribute-value grammars using an informative sample
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Probabilistic representation of formal languages
SWAT '69 Proceedings of the 10th Annual Symposium on Switching and Automata Theory (swat 1969)
Issues in Learning Language in Logic
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
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We show how partial models of natural language syntax (manually written DCGs, with parameters estimated from a parsed corpus) can be automatically extended when trained upon raw text (using MDL). We also show how we can use a parsed corpus as an alternative constraint upon learning. Empirical evaluation suggests that a parsed corpus is more informative than a MDL-based prior. However, best results are achieved when the learner is supervised with a compressionbased prior and a parsed corpus.