Probabilistic inference techniques can be used to estimate variable bias, or the proportion of solutions to a given SAT problem that fix a variable positively or negatively. Metho...
This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...
We describe a novel integration of Planning with Probabilistic State Estimation and Execution resulting in a unified representational and computational framework based on declarat...
Conor McGann, Frederic Py, Kanna Rajan, John Ryan,...
—This paper compares and illustrates the use of manually and automatically assigned descriptors on German documents extracted from the GIRT Corpus. A second objective is to analy...
Abstract. This paper presents an algorithm for the estimation of multiple regions with unknown shapes and positions using multiple active contour models (ACM’s). The algorithm or...