New approaches for boosting to uniformity
  The use of multivariate classifiers has become commonplace in particle physics. To enhance the performance, a series of classifiers is typically trained; this is a technique known as boosting. This paper explores several novel boosting methods that have been designed to produce a uniform selection efficiency in a chosen multivariate space. Such algorithms have a wide range of applications in particle physics, from producing uniform signal selection efficiency across a Dalitz-plot to avoiding the creation of false signal peaks in an invariant mass distribution when searching for new particles. 
Alex Rogozhnikov, Aleksandar Bukva, Vladimir Gligorov, Andrey   Ustyuzhanin and Mike Williams
hep-ex