Limitations and Future Trends in Neural Computation

Author/creator Ablameyko, Sergey, 1956- Editor
Other author Gori, Marco Editor
Other author Goras, Liviu Editor
Format Electronic
Publication InfoFairfax : IOS Press, Incorporated
Description245 p. ill 24.000 x 017.000 cm.
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

SeriesNATO-3 Science Series-Computer and Systems Sciences Ser. Vol. 186
Summary Annotation This book reports critical analyses on complexity issues in the continuum setting and on generalization to new examples, which are two basic milestones in learning from examples in connectionist models. The problem of loading the weights of neural networks, which is often framed as continuous optimization, has been the target of many criticisms, since the potential solution of any learning problem is severely limited by the presence of local minimal in the error function. The maturity of the field requires to convert the quest for a general solution to all learning problems into the understanding of which learning problems are likely to be solved efficiently. Likewise, the notion of efficient solution needs to be formalized so as to provide useful comparisons with the traditional theory of computational complexity in the discrete setting. The book covers these topics focussing also on recent developments in computational mathematics, where interesting notions of computational complexity emerge in the continuum setting.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2003101038
ISBN9781586033248
ISBN1586033247 (Trade Cloth) Active Record
Standard identifier# 9781586033248
Stock number00085221

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