We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
When envisaging new digital instruments, designers do not have to limit themselves to their sonic capabilities (which can be absolutely any), not even to their algorithmic power; ...
Abstract This paper investigates whether a machine can automatically learn the task of finding, within a large collection of candidate responses, the answers to questions. The lea...
Adam L. Berger, Rich Caruana, David Cohn, Dayne Fr...
We study the relative best-case performance of DPLL-based structure-aware SAT solvers in terms of the power of the underlying proof systems. The systems result from (i) varying th...
Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes ...
Jose M. Alvarez, Theo Gevers, Yann LeCun, Antonio ...