Buch, Englisch, Band 3264, 296 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 470 g
7th International Colloquium, ICGI 2004, Athens, Greece, October 11-13, 2004. Proceedings
Buch, Englisch, Band 3264, 296 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 470 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-540-23410-4
Verlag: Springer Berlin Heidelberg
estimations of probabilistic grammars.
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Research
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Fachgebiete
Weitere Infos & Material
Invited Papers.- Learning and Mathematics.- Learning Finite-State Models for Machine Translation.- The Omphalos Context-Free Grammar Learning Competition.- Regular Papers.- Mutually Compatible and Incompatible Merges for the Search of the Smallest Consistent DFA.- Faster Gradient Descent Training of Hidden Markov Models, Using Individual Learning Rate Adaptation.- Learning Mild Context-Sensitiveness: Toward Understanding Children’s Language Learning.- Learnability of Pregroup Grammars.- A Markovian Approach to the Induction of Regular String Distributions.- Learning Node Selecting Tree Transducer from Completely Annotated Examples.- Identifying Clusters from Positive Data.- Introducing Domain and Typing Bias in Automata Inference.- Analogical Equations in Sequences: Definition and Resolution.- Representing Languages by Learnable Rewriting Systems.- A Divide-and-Conquer Approach to Acquire Syntactic Categories.- Grammatical Inference Using Suffix Trees.- Learning Stochastic Finite Automata.- Navigation Pattern Discovery Using Grammatical Inference.- A Corpus-Driven Context-Free Approximation of Head-Driven Phrase Structure Grammar.- Partial Learning Using Link Grammars Data.- eg-GRIDS: Context-Free Grammatical Inference from Positive Examples Using Genetic Search.- The Boisdale Algorithm – An Induction Method for a Subclass of Unification Grammar from Positive Data.- Learning Stochastic Deterministic Regular Languages.- Polynomial Time Identification of Strict Deterministic Restricted One-Counter Automata in Some Class from Positive Data.- Poster Papers.- Learning Syntax from Function Words.- Running FCRPNI in Efficient Time for Piecewise and Right Piecewise Testable Languages.- Extracting Minimum Length Document Type Definitions Is NP-Hard.- Learning DistinguishableLinear Grammars from Positive Data.- Extending Incremental Learning of Context Free Grammars in Synapse.- Identifying Left-Right Deterministic Linear Languages.- Efficient Learning of k-Reversible Context-Free Grammars from Positive Structural Examples.- An Analysis of Examples and a Search Space for PAC Learning of Simple Deterministic Languages with Membership Queries.
