Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Abstract. Recent efforts in robust estimation of the two-view relation have focused on uncalibrated cameras with no prior knowledge of pose. However, in practice robotic vehicles t...
A significant problem encounteredwhen building Augmented Reality (AR) systems is that all spatial knowledge about the world has uncertainty associated with it. This uncertainty m...
Enylton Machado Coelho, Blair MacIntyre, Simon Jul...
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical formulation, however...