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Limitations and future trends in neural computation /

This work 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. It also covers up-to-date developments in computational mathematics.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: NATO Advanced Research Workshop on Limitations and Future Trends in Neural Computation Siena, Italy
Otros Autores: Ablameyko, Sergey, 1956-
Formato: Electrónico Congresos, conferencias eBook
Idioma:Inglés
Publicado: Amsterdam ; Burke, VA : Tokyo : IOS Press ; Ohmsha, ©2003.
Colección:NATO science series. Computer and systems sciences ; v. 186.
Temas:
Acceso en línea:Texto completo

MARC

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111 2 |a NATO Advanced Research Workshop on Limitations and Future Trends in Neural Computation  |d (2001 :  |c Siena, Italy) 
245 1 0 |a Limitations and future trends in neural computation /  |c edited by Sergey Ablameyko [and others]. 
260 |a Amsterdam ;  |a Burke, VA :  |b IOS Press ;  |a Tokyo :  |b Ohmsha,  |c ©2003. 
300 |a 1 online resource (ix, 245 pages) :  |b illustrations 
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490 1 |a NATO science series. Series III, Computer and systems sciences,  |x 1387-6694 ;  |v v. 186 
500 |a "Published in cooperation with NATO Scientific Affairs Division." 
504 |a Includes bibliographical references and index. 
505 0 |a Cover; Title page; Preface; Contents; Chapter 1. Continuous Problem Solving and Computational Suspiciousness; Chapter 2. The Complexity of Computing with Continuous Time Devices; Chapter 3. Energy-Based Computation with Symmetric Hopfield Nets; Chapter 4. Computational Complexity and the Elusiveness of Global Optima; Chapter 5. Impact of Neural Networks on Signal Processing and Communications; Chapter 6. From Clustering Data to Traveling as a Salesman: Empirical Risk Approximation as a Learning Theory; Chapter 7. Learning High-dimensional Data. 
520 |a This work 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. It also covers up-to-date developments in computational mathematics. 
588 0 |a Print version record. 
546 |a English. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Neural networks (Computer science)  |v Congresses. 
650 0 |a Neural computers  |v Congresses. 
650 6 |a Réseaux neuronaux (Informatique)  |v Congrès. 
650 6 |a Ordinateurs neuronaux  |v Congrès. 
650 7 |a COMPUTERS  |x Neural Networks.  |2 bisacsh 
650 7 |a Neural computers  |2 fast 
650 7 |a Neural networks (Computer science)  |2 fast 
655 7 |a Conference papers and proceedings  |2 fast 
700 1 |a Ablameyko, Sergey,  |d 1956- 
758 |i has work:  |a Limitations and Future Trends in Neural Computation (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCYxBrpYQ6QfcP3GcmJVCFC  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a NATO Advanced Research Workshop on Limitations and Future Trends in Neural Computation (2001 : Siena, Italy).  |t Limitations and future trends in neural computation.  |d Amsterdam ; Burke, VA : IOS Press ; Tokyo : Ohmsha, ©2003  |w (DLC) 2003101038 
830 0 |a NATO science series.  |n Series III,  |p Computer and systems sciences ;  |v v. 186.  |x 1387-6694 
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