Algorithmic decision making is employed in an increasing number of real-world applications
to aid human decision making. While it has shown considerable promise in terms of …

Machine learning models are becoming pervasive in high-stakes applications. Despite their
clear benefits in terms of performance, the models could show discrimination against …

Automated data-driven decision making systems are increasingly being used to assist, or
even replace humans in many settings. These systems function by learning from historical …

Conventional GEO satellite communication systems rely on a multibeam foot-print with a
uniform resource allocation to provide connectivity to users. However, applying uniform …

Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian
applications. Equipped with diverse communication payloads, UAVs cooperating with …

Spikes and rhythms organize control and communication in the animal world, in contrast to
the bits and clocks of digital technology. As continuous-time signals that can be counted …

The adoption of automated, data-driven decision making in an ever expanding range of
applications has raised concerns about its potential unfairness towards certain social …

We introduce the Suggest-and-Improve framework for general nonconvex quadratically
constrained quadratic programs (QCQPs). Using this framework, we generalize a number of …

In public media as well as in scientific publications, the term\emph {bias} is used in
conjunction with machine learning in many different contexts, and with many different …

Massive access for Internet-of-Things (IoT) in beyond 5G networks represents a daunting
challenge for conventional bandwidth-limited technologies. Millimeter-wave technologies …