| Description |
1 online resource (xviii, 248 pages) : illustrations |
| Series |
Adaptive computation and machine learning |
|
Adaptive computation and machine learning.
|
| Contents |
Regression -- Classification -- Covariance functions -- Model selection and adaptation of hyperparameters -- Relationships between GPs and other models -- Theoretical perspectives -- Approximation methods for large datasets -- Appendix A : Mathematical background -- Appendix B : Guassian Markov processes |
| Summary |
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics."--Jacket |
| Analysis |
COMPUTER SCIENCE/Machine Learning & Neural Networks |
|
neurale netwerken |
|
neural networks |
|
statistiek |
|
statistics |
|
gegevensverwerking |
|
data processing |
|
patroonherkenning |
|
pattern recognition |
|
kunstmatige intelligentie |
|
artificial intelligence |
|
Information and Communication Technology (General) |
|
Informatie- en communicatietechnologie (algemeen) |
| Bibliography |
Includes bibliographical references (pages 223-238) and indexes |
| Notes |
English |
|
Print version record |
| Subject |
Gaussian processes -- Data processing
|
|
Machine learning -- Mathematical models
|
|
MATHEMATICS -- Probability & Statistics -- Stochastic Processes.
|
|
Gaussian processes -- Data processing
|
|
Machine learning -- Mathematical models
|
|
Gauß-Prozess
|
|
Maschinelles Lernen
|
| Form |
Electronic book
|
| Author |
Williams, Christopher K. I.
|
| ISBN |
9780262256834 |
|
0262256835 |
|
1423769902 |
|
9781423769903 |
|
9780262182539 |
|
026218253X |
|
9786612097966 |
|
6612097965 |
|
1282097962 |
|
9781282097964 |
|
9786612096709 |
|
6612096705 |
|
0262261073 |
|
9780262261074 |
|
