E-Book, Englisch, Band 1891, 316 Seiten, eBook
Oliveira Grammatical Inference: Algorithms and Applications
2000
ISBN: 978-3-540-45257-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
5th International Colloquium, ICGI 2000, Lisbon, Portugal, September 11-13, 2000 Proceedings
E-Book, Englisch, Band 1891, 316 Seiten, eBook
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-540-45257-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
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Research
Autoren/Hrsg.
Weitere Infos & Material
Inference of Finite-State Transducers by Using Regular Grammars and Morphisms.- Computational Complexity of Problems on Probabilistic Grammars and Transducers.- Efficient Ambiguity Detection in C-NFA.- Learning Regular Languages Using Non Deterministic Finite Automata.- Smoothing Probabilistic Automata: An Error-Correcting Approach.- Inferring Subclasses of Contextual Languages.- Permutations and Control Sets for Learning Non-regular Language Families.- On the Complexity of Consistent Identification of Some Classes of Structure Languages.- Computation of Substring Probabilities in Stochastic Grammars.- A Comparative Study of Two Algorithms for Automata Identification.- The Induction of Temporal Grammatical Rules from Multivariate Time Series.- Identification in the Limit with Probability One of Stochastic Deterministic Finite Automata.- Iterated Transductions and Efficient Learning from Positive Data: A Unifying View.- An Inverse Limit of Context-Free Grammars – A New Approach to Identifiability in the Limit.- Synthesizing Context Free Grammars from Sample Strings Based on Inductive CYK Algorithm.- Combination of Estimation Algorithms and Grammatical Inference Techniques to Learn Stochastic Context-Free Grammars.- On the Relationship between Models for Learning in Helpful Environments.- Probabilistic k-Testable Tree Languages.- Learning Context-Free Grammars from Partially Structured Examples.- Identification of Tree Translation Rules from Examples.- Counting Extensional Differences in BC-Learning.- Constructive Learning of Context-Free Languages with a Subpansive Tree.- A Polynomial Time Learning Algorithm of Simple Deterministic Languages via Membership Queries and a Representative Sample.- Improve the Learning of Subsequential Transducers by Using Alignments andDictionaries.