Overview

This volume includes some of the key research papers in thearea of machine learning produced at MIT and Siemens duringa three-year joint research effort. It includes papers onmany different styles of machine learning, organized intothree parts.Part I, theory, includes three papers on theoretical aspectsof machine learning. The first two use the theory ofcomputational complexity to derive some fundamental limitson what isefficiently learnable. The third provides anefficient algorithm for identifying finite automata.Part II, artificial intelligence and symbolic learningmethods, includes five papers giving an overview of thestate of the art and future developments in the field ofmachine learning, a subfield of artificial intelligencedealing with automated knowledge acquisition and knowledgerevision.Part III, neural and collective computation, includes fivepapers sampling the theoretical diversity and trends in thevigorous new research field of neural networks: massivelyparallel symbolic induction, task decomposition throughcompetition, phoneme discrimination, behavior-basedlearning, and self-repairing neural networks.

ISBN-13

9783540564836

ISBN-10

3540564837

Weight

0.91 Pounds

Dimensions

6.10 x 0.65 x 9.25 In

List Price

$54.99

Edition

1st Edition

Format

Paperback

Language

English

Pages

viii, 276 pages

Publisher

Springer

Published On

1993-03-30



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