This paper gives an overview of the majorization-minimization (MM) algorithmic framework,
which can provide guidance in deriving problem-driven algorithms with low computational …

A comprehensive and invaluable guide to 5G technology, implementation and practice in
one single volume. For all things 5G, this book is a must-read. Signal processing techniques …

In this paper, we study a probabilistically robust transmit optimization problem under
imperfect channel state information (CSI) at the transmitter and under the multiuser multiple …

The purpose of this survey is to serve both as a gentle introduction and a coherent overview
of state-of-the-art Frank--Wolfe algorithms, also called conditional gradient algorithms, for …

We propose a novel decomposition framework for the distributed optimization of general
nonconvex sum-utility functions arising naturally in the system design of wireless multi-user …

Two key impediments to reconfigurable intelligent surface (RIS)-aided vehicular
communications are, respectively, the double fading experienced by the signal on RIS-aided …

Federated learning is a communication-efficient training process that alternate between
local training at the edge devices and averaging of the updated local model at the center …

We study the safe reinforcement learning problem with nonlinear function approximation,
where policy optimization is formulated as a constrained optimization problem with both the …

Mobile-edge computing (MEC) is considered as a promising technology to reduce the
energy consumption (EC) and task accomplishment latency of smart mobile user …

This paper considers stochastic optimization problems for a large class of objective
functions, including convex and continuous submodular. Stochastic proximal gradient …