We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
This paper describes a framework for selecting the optimal call mix to be admitted while employing a bandwidth degradation policy in a wireless cellular network. The optimal proper...
—In this paper, we investigate methods for reducing the likelihood that a message transmitted between two multiantenna nodes is intercepted by an undetected eavesdropper. In part...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
We propose a joint channel and data estimation scheme which does not require the training data in multicarrier direct-sequence multiple access (MC-DS/CDMA) systems. In order to eli...