We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
A wide variety of techniques for visual navigation using robot-mounted cameras have been described over the past several decades, yet adoption of optical flow navigation technique...
Jason Campbell, Rahul Sukthankar, Illah R. Nourbak...