Advances in learning theory: methods, models, and applications
Gespeichert in:
| Körperschaft: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
IOS Press
c2003
|
| Schriftenreihe: | NATO science series
v. 190 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | "Proceedings of the NATO Advanced Study Institute on Learning Theory and Practice, 8-19 July 2002, Leuven, Belgium"--T.p. verso. - "Published in cooperation with NATO Scientific Affairs Division.". - Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002 Includes bibliographical references and indexes Cover; Title page; Preface; Organizing committee; List of chapter contributors; Contents; 1 An Overview of Statistical Learning Theory; 2 Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem; 3 Cucker Smale Learning Theory in Besov Spaces; 4 High-dimensional Approximation by Neural Networks; 5 Functional Learning through Kernels; 6 Leave-one-out Error and Stability of Learning Algorithms with Applications; 7 Regularized Least-Squares Classification; 8 Support Vector Machines: Least Squares Approaches and Extensions This text details advances in learning theory that relate to problems studied in neural networks, machine learning, mathematics and statistics |
| Beschreibung: | 1 Online-Ressource (xxi, 415 p.) |
| ISBN: | 1586033417 9781586033415 427490587X 9784274905872 1417511397 9781417511396 1601294018 9781601294012 |
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| 500 | |a Includes bibliographical references and indexes | ||
| 500 | |a Cover; Title page; Preface; Organizing committee; List of chapter contributors; Contents; 1 An Overview of Statistical Learning Theory; 2 Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem; 3 Cucker Smale Learning Theory in Besov Spaces; 4 High-dimensional Approximation by Neural Networks; 5 Functional Learning through Kernels; 6 Leave-one-out Error and Stability of Learning Algorithms with Applications; 7 Regularized Least-Squares Classification; 8 Support Vector Machines: Least Squares Approaches and Extensions | ||
| 500 | |a This text details advances in learning theory that relate to problems studied in neural networks, machine learning, mathematics and statistics | ||
| 650 | 4 | |a Computational learning theory | |
| 650 | 4 | |a Machine learning / Mathematical models | |
| 650 | 4 | |a Apprentissage informatique, Théorie de l' / Congrès | |
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Datensatz im Suchindex
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| dewey-full | 006.3/1 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/1 |
| dewey-search | 006.3/1 |
| dewey-sort | 16.3 11 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| isbn | 1586033417 9781586033415 427490587X 9784274905872 1417511397 9781417511396 1601294018 9781601294012 |
| language | English |
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| spelling | NATO Advanced Study Institute on Learning Theory and Practice <2002, Louvain, Belgium> Verfasser aut Advances in learning theory methods, models, and applications edited by Johan Suykens ... [et al.] Amsterdam IOS Press c2003 1 Online-Ressource (xxi, 415 p.) txt rdacontent c rdamedia cr rdacarrier NATO science series v. 190 "Proceedings of the NATO Advanced Study Institute on Learning Theory and Practice, 8-19 July 2002, Leuven, Belgium"--T.p. verso. - "Published in cooperation with NATO Scientific Affairs Division.". - Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002 Includes bibliographical references and indexes Cover; Title page; Preface; Organizing committee; List of chapter contributors; Contents; 1 An Overview of Statistical Learning Theory; 2 Best Choices for Regularization Parameters in Learning Theory: On the Bias-Variance Problem; 3 Cucker Smale Learning Theory in Besov Spaces; 4 High-dimensional Approximation by Neural Networks; 5 Functional Learning through Kernels; 6 Leave-one-out Error and Stability of Learning Algorithms with Applications; 7 Regularized Least-Squares Classification; 8 Support Vector Machines: Least Squares Approaches and Extensions This text details advances in learning theory that relate to problems studied in neural networks, machine learning, mathematics and statistics Computational learning theory Machine learning / Mathematical models Apprentissage informatique, Théorie de l' / Congrès Apprentissage automatique / Modèles mathématiques / Congrès COMPUTERS / Enterprise Applications / Business Intelligence Tools bisacsh COMPUTERS / Intelligence (AI) & Semantics bisacsh Computational learning theory fast Machine learning / Mathematical models fast Mathematisches Modell Computational learning theory Congresses Machine learning Mathematical models Congresses (DE-588)1071861417 Konferenzschrift gnd-content Suykens, Johan A. K. Sonstige oth http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=110129 Aggregator Volltext |
| spellingShingle | Advances in learning theory methods, models, and applications Computational learning theory Machine learning / Mathematical models Apprentissage informatique, Théorie de l' / Congrès Apprentissage automatique / Modèles mathématiques / Congrès COMPUTERS / Enterprise Applications / Business Intelligence Tools bisacsh COMPUTERS / Intelligence (AI) & Semantics bisacsh Computational learning theory fast Machine learning / Mathematical models fast Mathematisches Modell Computational learning theory Congresses Machine learning Mathematical models Congresses |
| subject_GND | (DE-588)1071861417 |
| title | Advances in learning theory methods, models, and applications |
| title_auth | Advances in learning theory methods, models, and applications |
| title_exact_search | Advances in learning theory methods, models, and applications |
| title_full | Advances in learning theory methods, models, and applications edited by Johan Suykens ... [et al.] |
| title_fullStr | Advances in learning theory methods, models, and applications edited by Johan Suykens ... [et al.] |
| title_full_unstemmed | Advances in learning theory methods, models, and applications edited by Johan Suykens ... [et al.] |
| title_short | Advances in learning theory |
| title_sort | advances in learning theory methods models and applications |
| title_sub | methods, models, and applications |
| topic | Computational learning theory Machine learning / Mathematical models Apprentissage informatique, Théorie de l' / Congrès Apprentissage automatique / Modèles mathématiques / Congrès COMPUTERS / Enterprise Applications / Business Intelligence Tools bisacsh COMPUTERS / Intelligence (AI) & Semantics bisacsh Computational learning theory fast Machine learning / Mathematical models fast Mathematisches Modell Computational learning theory Congresses Machine learning Mathematical models Congresses |
| topic_facet | Computational learning theory Machine learning / Mathematical models Apprentissage informatique, Théorie de l' / Congrès Apprentissage automatique / Modèles mathématiques / Congrès COMPUTERS / Enterprise Applications / Business Intelligence Tools COMPUTERS / Intelligence (AI) & Semantics Mathematisches Modell Computational learning theory Congresses Machine learning Mathematical models Congresses Konferenzschrift |
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