Publishing Partner: Cambridge University Press CUP Extra Wiley-Blackwell Publisher Login
amazon logo
More Info


New from Oxford University Press!

ad

Words in Time and Place: Exploring Language Through the Historical Thesaurus of the Oxford English Dictionary

By David Crystal

Offers a unique view of the English language and its development, and includes witty commentary and anecdotes along the way.


New from Cambridge University Press!

ad

Thesaurus of English Words and Phrases

By Peter Mark Roget

This book "supplies a vocabulary of English words and idiomatic phrases 'arranged … according to the ideas which they express'. The thesaurus, continually expanded and updated, has always remained in print, but this reissued first edition shows the impressive breadth of Roget's own knowledge and interests."


New from Brill!

ad

The Brill Dictionary of Ancient Greek

By Franco Montanari

Coming soon: The Brill Dictionary of Ancient Greek by Franco Montanari is the most comprehensive dictionary for Ancient Greek to English for the 21st Century. Order your copy now!


Book Information

   
Sun Image

Title: The Informational Complexity of Learning
Written By: Partha Niyogi
URL: http://www.wkap.nl/book.htm/0-7923-8081-9
Description:

Among other topics, The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar brings together two important but very different learning problems within the same analytical framework. The first concerns the problem of learning functional mappings using neural networks, followed by learning natural language grammars in the principles and parameters tradition of Chomsky. These two learning problems are seemingly very different. Neural networks are real-valued, infinite-dimensional, continuous mappings. On the other hand, grammars are boolean-valued, finite-dimensional, discrete (symbolic) mappings. Furthermore the research communities that work in the two areas almost never overlap. The book's objective is to bridge this gap. It uses the formal techniques developed in statistical learning theory and theoretical computer science over the last decade to analyze both kinds of learning problems. By asking the same question - how much information does it take to learn? - of both problems, it highlights their similarities and differences. Specific results include model selection in neural networks, active learning, language learning and evolutionary models of language change. The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar is a very interdisciplinary work. Anyone interested in the interaction of computer science and cognitive science should enjoy the book. Researchers in artificial intelligence, neural networks, linguistics, theoretical computer science, and statistics will find it particularly relevant.

Publication Year: 1997
Publisher: Kluwer
Review: Not available for review. If you would like to review a book on The LINGUIST List, please login to view the AFR list.
BibTex: View BibTex record
Linguistic Field(s): Computational Linguistics
Linguistic Theories
Psycholinguistics
Syntax
Neurolinguistics
Issue: All announcements sent out by The LINGUIST List are emailed to our subscribers and archived with the Library of Congress.
Click here to see the original emailed issue.

Versions:
Format: Hardback
ISBN: 0792380819
ISBN-13: N/A
Pages: 248 p
Prices: EUR 103.00 / USD 119.00 / GBP