We present a new Monte Carlo method for solving the light transport problem, inspired by the Metropolis sampling method in computational physics. To render an image, we generate a...
In a sensor network there are many paths between a source and a destination. An efficient method to explore and navigate in the ‘path space’ can help many important routing p...
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
We provide a principle for semi-supervised learning based on optimizing the rate of communicating labels for unlabeled points with side information. The side information is expres...
— Mobile robot localization and navigation requires a map - the robot’s internal representation of the environment. A common problem is that path planning becomes very ineffic...