Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
An image representation framework based on structured sparse model selection is introduced in this work. The corresponding modeling dictionary is comprised of a family of learned ...
Abstract. Differential motion estimation is based on detecting brightness changes in local image structures. Filters approximating the local gradient are applied to the image seque...
The discrete multitone (DMT)transceivers have enjoyed great success in high speed data transmission. It is known that when the cyclicprefix is no shorterthan the channel impulse r...
This paper discusses a program synthesis system to facilitate the generation of high-performance parallel programs for a class of computations encountered in quantum chemistry and...
Gerald Baumgartner, David E. Bernholdt, Daniel Coc...