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Grammatical Inference(文法推论:算法与应用/会议录)

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Grammatical Inference(文法推论:算法与应用/会议录)

最 低 价:¥488.16

原   价:¥542.40

GeorgiosPaliouras , YasubumiSakakibara 著

商品详情

This book constitutes the refereed proceedings of the 7th International Colloquium on Grammatical Inference, ICGI 2004, held in Athens, Greece in October 2004.
The 20 revised full papers and 8 revised poster papers presented together with 3 invited contributions were carefully reviewed and selected from 45 submissions. The topics of the papers presented range from theoretical results of learning algorithms to innovative applications of grammatical inference and from learning several interesting classes of formal grammars to estimations of probabilistic grammars.

Invited Papers
Learning and Mathematics
Learning FiniteState 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:ContextFree 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
……
Author Index

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