Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
Solving linear systems with a large number of variables is at the core of many scienti c problems. Parallel processing techniques for solving such systems have received much attent...
Arun Nagari, Itamar Elhanany, Ben Thompson, Fangxi...
Source and destination location privacy is a challenging and important problem in sensor networks. Nevertheless, privacy preserving communication in sensor networks is still a vir...
Yingchang Xiang, Dechang Chen, Xiuzhen Cheng, Kai ...
For a robot, the ability to get from one place to another is one of the most basic skills. However, locomotion on legged robots is a challenging multidimensional control problem. ...
The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 200...