Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose and study block compressed sensing for natural images, where i...
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
—We consider a system with a single base station communicating with multiple users over orthogonal channels while being assisted by multiple relays. Several recent works have sug...
Abstract— We present a novel approach to compute collisionfree paths for multiple robots subject to local coordination constraints. More specifically, given a set of robots, the...
Russell Gayle, William Moss, Ming C. Lin, Dinesh M...