@article{2087,
  title = {Moment Inequalities for Functions of Independent Random Variables},
  journal = {To appear in Annals of Probability},
  abstract = {A general method for obtaining moment inequalities for functions
  of independent random variables is presented. It is a
  generalization of the entropy method which has been used to
  derive concentration
  inequalities for such functions cite{BoLuMa01}, and is based on
  a generalized tensorization inequality due to Lata{l}a and Oleszkiewicz
  cite{LaOl00}.
  The new inequalities prove to be a versatile tool in a
  wide range of applications.
  We illustrate the power of the method by showing how
  it can be used to effortlessly re-derive classical
  inequalities including
  Rosenthal and Kahane-Khinchine-type inequalities for sums
  of independent random variables, moment inequalities for suprema
  of empirical processes, and moment inequalities for Rademacher chaos
  and $U$-statistics. Some of these corollaries are apparently new.
  In particular, we generalize Talagrands exponential inequality
  for Rademacher chaos of order two to any order.
  We also discuss applications for other complex functions
  of independent random variables, such as suprema of boolean polynomials
  which include, as special cases, subgraph counting problems in
  random graphs.},
  volume = {33},
  pages = {514-560},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  year = {2005},
  author = {Boucheron, S. and Bousquet, O. and Lugosi, G. and Massart, P.}
}