We propose a framework for blind multiple filter estimation from convolutive mixtures, exploiting the time-domain sparsity of the mixing filters and the disjointness of the sources...
This paper describes the study conducted to design and evaluate a two-level on-line scheduler to dynamically schedule a stream of sequential and multi-threaded batch jobs on large...
Marco Pasquali, Ranieri Baraglia, Gabriele Capanni...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Underwater wireless sensor networks consist of a certain number of sensors and vehicles that interact to collect data and perform collaborative tasks. Designing energy-efficient r...
Design and simulation of future mobile networks will center around human interests and behavior. We propose a design paradigm for mobile networks driven by realistic models of use...
Saeed Moghaddam, Ahmed Helmy, Sanjay Ranka, Manas ...