Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse the Sampling Importanc...
This article proposes a stochastic version of the matching pursuit algorithm for Bayesian variable selection in linear regression. In the Bayesian formulation, the prior distributi...
— The paper proposes several improvements on the Direction of Gradient (DOG) algorithm proposed in [1] for detecting and localizing a biochemical source with moving sensors. In p...
The efforts of an expert to parallelize and optimize a dense linear algebra algorithm for distributed-memory targets are largely mechanical and repetitive. We demonstrate that the...
Bryan Marker, Andy Terrel, Jack Poulson, Don S. Ba...
k- and t-optimality algorithms [9, 6] provide solutions to DCOPs that are optimal in regions characterized by its size and distance respectively. Moreover, they provide quality gu...