We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Abstract— Robust ego-motion estimation in urban environments is a key prerequisite for making a robot truly autonomous, but is not easily achievable as there are two motions invo...
In order to solve future Multi Level Security (MLS) problems, we have developed a solution based on the DARPA Polymorphous Computing Architecture (PCA). MLS-PCA uses a novel distr...
: Statistical shape models are powerful tools for model-based segmentation and have been sucessfully applied to the segmentation of various structures in medical images. Though the...