Recently, many researchers have worked on tabletop systems. One issue with tabletop interfaces is how to control the table without using conventional desktop input devices such as ...
We consider the context of decision support for schedule modification after the computation off-line of a predictive optimal (or near optimal) schedule. The purpose of this work i...
Abstract-- We report our experiences in designing and implementing several hardware Trojans within the framework of the Embedded System Challenge competition that was held as part ...
The joint-sparse recovery problem aims to recover, from sets of compressed measurements, unknown sparse matrices with nonzero entries restricted to a subset of rows. This is an ex...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...