Topics in Grammatical Inference

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Computer Science, General Computing
Cover of the book Topics in Grammatical Inference by , Springer Berlin Heidelberg
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783662483954
Publisher: Springer Berlin Heidelberg Publication: May 4, 2016
Imprint: Springer Language: English
Author:
ISBN: 9783662483954
Publisher: Springer Berlin Heidelberg
Publication: May 4, 2016
Imprint: Springer
Language: English

This book explains advanced theoretical and application-related issues in grammatical inference, a research area inside the inductive inference paradigm for machine learning. The first three chapters of the book deal with issues regarding theoretical learning frameworks; the next four chapters focus on the main classes of formal languages according to Chomsky's hierarchy, in particular regular and context-free languages; and the final chapter addresses the processing of biosequences.

 

The topics chosen are of foundational interest with relatively mature and established results, algorithms and conclusions. The book will be of value to researchers and graduate students in areas such as theoretical computer science, machine learning, computational linguistics, bioinformatics, and cognitive psychology who are engaged with the study of learning, especially of the structure underlying the concept to be learned. Some knowledge of mathematics and theoretical computer science, including formal language theory, automata theory, formal grammars, and algorithmics, is a prerequisite for reading this book.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book explains advanced theoretical and application-related issues in grammatical inference, a research area inside the inductive inference paradigm for machine learning. The first three chapters of the book deal with issues regarding theoretical learning frameworks; the next four chapters focus on the main classes of formal languages according to Chomsky's hierarchy, in particular regular and context-free languages; and the final chapter addresses the processing of biosequences.

 

The topics chosen are of foundational interest with relatively mature and established results, algorithms and conclusions. The book will be of value to researchers and graduate students in areas such as theoretical computer science, machine learning, computational linguistics, bioinformatics, and cognitive psychology who are engaged with the study of learning, especially of the structure underlying the concept to be learned. Some knowledge of mathematics and theoretical computer science, including formal language theory, automata theory, formal grammars, and algorithmics, is a prerequisite for reading this book.

More books from Springer Berlin Heidelberg

Cover of the book Green Building by
Cover of the book Economics as Moral Science by
Cover of the book Cancer Therapy by
Cover of the book Luftschall aus dem Schienenverkehr by
Cover of the book Carl Størmer by
Cover of the book Air Instrument Surgery by
Cover of the book Cosmic Ray Diffusion in the Galaxy and Diffuse Gamma Emission by
Cover of the book Endocrines and Osmoregulation by
Cover of the book Nonlinear Super-Resolution Nano-Optics and Applications by
Cover of the book Kommentar zur Musterberufsordnung der deutschen Ärzte (MBO) by
Cover of the book The Correctness-by-Construction Approach to Programming by
Cover of the book Dynamic Interaction of Train-Bridge Systems in High-Speed Railways by
Cover of the book Logistikmanagement by
Cover of the book Learning Pediatric Imaging by
Cover of the book Introduction to Wind Energy Systems by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy