Adaptive nonparametric estimation in heteroscedastic regression models.   Part 1: Sharp non-asymptotic Oracle inequalities
  An adaptive nonparametric estimation procedure is constructed for the estimation problem of heteroscedastic regression when the noise variance depends on the unknown regression. A non-asymptotic upper bound for a quadratic risk (an oracle inequality) is constructed. 
Leonid Galtchouk (IRMA), Serguey Pergamenshchikov (LMRS)