Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...
The most popular approaches for reconstructing phylogenetic trees attempt to solve NP-hard optimization criteria such as maximum parsimony (MP). Currently, the bestperforming heur...
Abstract—Most signal processing problems involve the challenging task of multidimensional probability density function (PDF) estimation. In this paper, we propose a solution to t...
Replicating data objects onto servers across a system can alleviate access delays. The selection of data objects and servers requires solving a constraint optimization problem, wh...