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[null,"1.","Record Nr.",null,"UNINA9910666795503321"]
[null,null,"Autore",null,"Rasmussen Carl Edward"]
[null,null,"Titolo",null,"Gaussian processes for machine learning / / Carl Edward Rasmussen, Christopher K.I. Williams"]
[null,null,"Pubbl/distr/stampa",null,"Cambridge, Mass., : MIT Press, c2006"]
[null,null,"ISBN",null,"0-262-26107-3"]
[{"$nulls":4},"9786612097966"]
[{"$nulls":4},"1-4237-6990-2"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"xviii, 248 p. : ill"]
[null,null,"Collana",null,"Adaptive computation and machine learning"]
[null,null,"Disciplina",null,"519.2/3"]
[null,null,"Soggetti",null,"Gaussian processes - Data processing"]
[{"$nulls":4},"Machine learning - Mathematical models"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Title from title screen."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. [223]-238) and indexes."]
[null,null,"Nota di contenuto",null,"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."]
[null,null,null,"Sommario/riassunto","A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines."]