Abstract. We explore a new general-purpose heuristic for nding highquality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-or...
Stefan Boettcher, Allon G. Percus, Michelangelo Gr...
Traditional approaches for modeling a closed manifold surface with either regular tensor-product or triangular splines (defined over an open planar domain) require decomposing th...
We propose a new Bayesian, stochastic tracking algorithm for the segmentation of blood vessels from 3D medical image data. Inspired by the recent developments in particle filterin...
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga...
A collaborative system must perform both processing and transmission tasks. We present a policy for scheduling these tasks on a single core that is inspired by studies of human pe...
In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...