3 accepted papers
We propose a novel parallel asynchronous algorithmic framework for the minimization of the sum of a smooth (nonconvex) function and a convex (nonsmooth) regularizer. The framework hinges on Successive Convex Approximation (SCA) techniques and on a novel probabilistic model which describes in a unifi…
The paper studies a general class of distributed dictionary learning (DL) problems where the learning task is distributed over a multi-agent network with (possibly) time-varying (non-symmetric) connectivity. This setting is relevant, for instance, in scenarios where massive amounts of data are not c…
The paper studies the max-min fair multicast multigroup beamforming problem in a multi-cell environment, with perfect (instantaneous or statistical) Channel State Information (CSI). We propose a new general distributed algorithmic framework based on INner Convex Approximations (INCA): the nonsmooth…