Machine Learning: From Theory to Applications: Cooperative Research at Siemens and MIT (Lecture Notes in Computer Science, Volume 661)

S.J. Hanson, et al., editors

ISBN 10: 0387564837 / ISBN 13: 9780387564838

Published by Springer-Verlag, 1993

About this Item

271 pp., paperback, ex library, else text and binding clean and tight. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Seller Inventory # ZB389159

Bibliographic Details

Title: Machine Learning: From Theory to ...

Publisher: Springer-Verlag

Publication Date: 1993

Condition: Good

About this title

Synopsis:

This volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what is efficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision. Part III, neural and collective computation, includes five papers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks.