@inbook{3d717772859c4fc48181e14f21627d32,
title = "Bayesian kernel methods",
abstract = "Bayesian methods allow for a simple and intuitive representation of the function spaces used by kernel methods. This chapter describes the basic principles of Gaussian Processes, their implementation and their connection to other kernel-based Bayesian estimation methods, such as the Relevance Vector Machine.",
author = "Smola, {Alexander J.} and Bernhard Sch{\"o}lkopf",
year = "2003",
doi = "10.1007/3-540-36434-x_3",
language = "English",
isbn = "9783540005292",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "65--117",
editor = "Shahar Mendelson and Smola, {Alexander J.}",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}