We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...
Sparse matrix operations achieve only small fractions of peak CPU speeds because of the use of specialized, indexbased matrix representations, which degrade cache utilization by i...
We propose an algorithm for automatically obtaining a segmentation of a rigid object in a sequence of images that are calibrated for camera pose and intrinsic parameters. Until re...
Neill D. F. Campbell, George Vogiatzis, Carlos Her...
—An important challenge in mobile sensor networks is to enable energy-efficient communication over a diversity of distances while being robust to wireless effects caused by node...
Jeremy Gummeson, Deepak Ganesan, Mark D. Corner, P...