In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Policy evaluation is a critical step in the approximate solution of large Markov decision processes (MDPs), typically requiring O(|S|3 ) to directly solve the Bellman system of |S...
We derive a novel method to determine the parameters for regularized super-resolution problems. The proposed approach relies on the Joint Maximum a Posteriori (JMAP) estimation te...
Electric Sheep is a distributed screen-saver that harnesses idle computers into a render farm with the purpose of animating and evolving artificial life-forms known as sheep. The...