@ARTICLE\{IMM2003-01511,
    author       = "D. Malzahn and M. Opper",
    title        = "Learning Curves and Bootstrap Estimates for Inference with Gaussian Processes: A Statistical Mechanics Study",
    year         = "2003",
    keywords     = "Bootstrap, Gaussian processes, learning curves, statistical physics, variational methods",
    pages        = "57-63",
    journal      = "Complexity",
    volume       = "8",
    editor       = "H. G. Schuster and K. Pawelzik",
    number       = "4",
    publisher    = "Wiley",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/1511-full.html",
    abstract     = "We employ the replica method of statistical physics to study the average 
case performance of learning systems. The new feature of our theory is 
that general distributions of data can be treated, which enables 
applications to real data. For a class of Bayesian prediction models 
which are based on Gaussian processes, we discuss Bootstrap estimates 
for learning curves."
}