In this paper we model the components of the compressive sensing (CS) problem using the Bayesian framework by utilizing a hierarchical form of the Laplace prior to model sparsity ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
The efficiency of Peer-to-Peer (P2P) systems is largely dependent on the overlay constructions. Due to the random selection of logical neighbors, there often exists serious topolog...
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
In repeated games with incomplete information, rational agents must carefully weigh the tradeoffs of advantageously exploiting their information to achieve a short-term gain versu...