Many applications in computer vision and pattern recognition involve drawing inferences on certain manifoldvalued parameters. In order to develop accurate inference algorithms on ...
Pavan K. Turaga, Ashok Veeraraghavan, Rama Chellap...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
An approach for incremental learning of a 3D scene from a single static video camera is presented in this paper. In particular, we exploit the presence of casual people walking in...
Diego Rother, Kedar A. Patwardhan, Guillermo Sapir...
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...
We propose a gossip-based distributed algorithm for Gaussian mixture learning, Newscast EM. The algorithm operates on network topologies where each node observes a local quantity ...