While the fifth-generation systems are being rolled out across the globe, researchers have
turned their attention to the exploration of radical next-generation solutions. At this early …

Existing communication systems exhibit inherent limitations in translating theory to practice
when handling the complexity of optimization for emerging wireless applications with high …

Future wireless communication networks tend to be intelligentized to accomplish the
missions that cannot be preprogrammed. In the new intelligent communication systems …

Signal processing, communications, and control have traditionally relied on classical
statistical modeling techniques. Such model-based methods tend to be sensitive to …

The fields of machine learning and mathematical programming are increasingly intertwined.
Optimization problems lie at the heart of most machine learning approaches. The Special …

This short monograph contains the material expanded from two tutorials that the authors
gave, one at APSIPA in October 2011 and the other at ICASSP in March 2012. Substantial …

Neural networks dominate the modern machine learning landscape, but their training and
success still suffer from sensitivity to empirical choices of hyperparameters such as model …

Reinforcement learning (RL) applications, where an agent can simply learn optimal
behaviors by interacting with the environment, are quickly gaining tremendous success in a …

The ever-increasing demand for wireless services and the continual improvements in
wireless technology has led to the emergence of different types of wireless networks. These …