In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the componen...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
This paper presents a novel approach to detect and track pedestrians and cars based on the combined information retrieved from a camera and a laser range scanner. Laser data points...
Luciano Spinello, Rudolph Triebel, Roland Siegwart
Abstract— Imitation learning in robots, also called programing by demonstration, has made important advances in recent years, allowing humans to teach context dependant motor ski...
We present a new algorithm to detect humans in still images utilizing covariance matrices as object descriptors. Since these descriptors do not lie on a vector space, well known m...
We extend the PAC-Bayes theorem to the sample-compression setting where each classifier is represented by two independent sources of information: a compression set which consists ...