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Autore: |
Rasmussen Carl Edward
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Titolo: |
Gaussian processes for machine learning / / Carl Edward Rasmussen, Christopher K.I. Williams
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Pubblicazione: | Cambridge, Mass., : MIT Press, c2006 |
Edizione: | 1st ed. |
Descrizione fisica: | xviii, 248 p. : ill |
Disciplina: | 519.2/3 |
Soggetto topico: | Gaussian processes - Data processing |
Machine learning - Mathematical models | |
Altri autori: |
WilliamsChristopher K. I
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Note generali: | Title from title screen. |
Nota di bibliografia: | Includes bibliographical references (p. [223]-238) and indexes. |
Nota di contenuto: | Intro -- Series Foreword -- Preface -- Symbols and Notation -- Chapter 1 Introduction -- Chapter 2 Regression -- Chapter 3 Classification -- Chapter 4 Covariance functions -- Chapter 5 Model Selection and Adaptation of Hyperparameters -- Chapter 6 Relationships between GPs and Other Models -- Chapter 7 Theoretical Perspectives -- Chapter 8 Approximation Methods for Large Datasets -- Chapter 9 Further Issues and Conclusions -- Appendix A Mathematical Background -- Appendix B Gaussian Markov Processes -- Appendix C Datasets and Code -- Bibliography -- Author Index -- Subject Index. |
Sommario/riassunto: | A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. |
Titolo autorizzato: | Gaussian processes for machine learning ![]() |
ISBN: | 0-262-26107-3 |
9786612097966 | |
1-4237-6990-2 | |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910666795503321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |