In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Since the de nition of the High Performance Fortran HPF standard, we have been maintaining a suite of application kernel codes with the aim of using them to evaluate the availabl...
A novel 3D shape matching method is proposed in this paper. We first extract angular and distance feature pairs from pre-processed 3D models, then estimate their kernel densities ...
Abstract— A disjoint support decomposition (DSD) is a representation of a Boolean function F obtained by composing two or more simpler component functions such that the component...
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...