Belief propagation (BP) is an increasingly popular method of performing approximate inference on arbitrary graphical models. At times, even further approximations are required, wh...
Alexander T. Ihler, John W. Fisher III, Alan S. Wi...
Since Bayesian network (BN) was introduced in the field of artificial intelligence in 1980s, a number of inference algorithms have been developed for probabilistic reasoning. Ho...
Selecting promising queries is the key to effective active learning. In this paper, we investigate selection techniques for the task of learning an equivalence relation where the ...
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
As shown in [7], optimal control problems with either ODE or PDE dynamics can be solved efficiently using a setting of consistent approximations obtained by numerical discretizati...