We describe a Markov chain Monte Carlo (MCMC)-based algorithm for sampling solutions to mixed Boolean/integer constraint problems. The focus of this work differs in two points from...
Abstract-- Sensor networks are typically unattended because of their deployment in hazardous, hostile or remote environments. This makes the problem of conserving energy at individ...
Rajgopal Kannan, Ramaraju Kalidindi, S. Sitharama ...
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
—When manufacturing nano-devices, defects are a certainty and reliability becomes a critical issue. Until now, the most pervasive methods used to address reliability, involve inj...
Abstract—In this paper we propose a novel statistical framework to model the impact of process variations on semiconductor circuits through the use of process sensitive test stru...