@techreport{2816,
  title = {Kernels, Associated Structures and Generalizations},
  abstract = {This paper gives a survey of results in the mathematical
  literature on positive definite kernels and their associated
  structures. We concentrate on properties which seem potentially
  relevant for Machine Learning and try to clarify some results that
  have been misused in the literature. Moreover we consider
  different lines of generalizations of positive definite kernels.
  Namely we deal with operator-valued kernels and present the
  general framework of Hilbertian subspaces of Schwartz which we use
  to introduce kernels which are distributions. Finally indefinite
  kernels and their associated reproducing kernel spaces are
  considered.},
  number = {127},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics, T{\"u}bingen, Germany},
  school = {Biologische Kybernetik},
  month = jul,
  year = {2004},
  author = {Hein, M. and Bousquet, O.},
  month_numeric = {7}
}