Abstract--Recurrent neural networks have become a prominent tool for optimizations including linear or nonlinear variational inequalities and programming, due to its regular mathem...
Over the past decade, automated systems dedicated to geopositioning have been the object of considerable development. Despite the success of these systems for many applications, th...
Jean-Marie Le Yaouanc, Eric Saux, Christophe Clara...
We present and analyze an agnostic active learning algorithm that works without keeping a version space. This is unlike all previous approaches where a restricted set of candidate...
Alina Beygelzimer, Daniel Hsu, John Langford, Tong...
—The suppression of late reverberation by spectral subtraction tends to degrade disproportionally low-level signal regions and signal transients. This work proposes two novel rel...
Abstract-- We study joint rate control and resource allocation with QoS provisioning that maximizes the total utility of secondary users in cognitive radio networks. We formulate a...