@inbook{d4e0cc4f33b94e1dbe59b32e7b62c766,
title = "Learning curves for Gaussian processes models: fluctuations and universality",
abstract = "Based on a statistical mechanics approach, we develop a method for approximately computing average case learning curves and their sample fluctuations for Gaussian process regression models. We give examples for the Wiener process and show that universal relations (that are independent of the input distribution) between error measures can be derived.",
keywords = "statistical, mechanics, computing average, learning curves, sample fluctuations, Gaussian process regression, Wiener process, universal relations, error measures",
author = "Dorthe Malzahn and Manfred Opper",
note = "The original publication is available at www.springerlink.com; Artificial Neural Networks 2001, ICANN 2001 ; Conference date: 21-08-2001 Through 25-08-2001",
year = "2001",
month = jan,
day = "1",
doi = "10.1007/3-540-44668-0_39",
language = "English",
isbn = "9783540424864",
volume = "2130",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "271--276",
editor = "G. Dorffner and H. Bischof and K. Hornik",
booktitle = "Artificial Neural Networks — ICANN 2001",
address = "Germany",
}