Automated market makers, first popularized by Hanson's logarithmic market scoring rule (or
LMSR) for prediction markets, have become important building blocks, called'primitives,'for …

This correspondence reveals the potential of reconfigurable intelligent surface (RIS) in anti-
jamming communications. In particular, we consider an aerial RIS (ARIS) that can be flexibly …

Providing formal guarantees of algorithmic fairness is of paramount importance to socially
responsible deployment of machine learning algorithms. In this work, we study formal …

Most modern large-scale multi-agent systems operate by taking actions based on local data
and cooperate by exchanging information over communication networks. Due to the …

Solar photocatalytic hydrogen production is considered a promising technology owing to its
sustainable nature, while facing the challenges of improving and maintaining photocatalytic …

We present DDTO--deferred-decision trajectory optimization--a framework for trajectory
generation with resilience to unmodeled uncertainties and contingencies. The key idea is to …

To ensure the operational reliability of power systems, it is important for wind speed signal
forecasting systems of wind turbines to be efficient, accurate and stable. This paper …

Preconditioning has long been a staple technique in optimization, often applied to reduce
the condition number of a matrix and speed up the convergence of algorithms. Although …

In this paper, we propose a cell-free scheme for unmanned-aerial-vehicle (UAV) base-
stations (BSs) to manage the severe intercell interference between aerial and terrestrial …

Convex programming plays a fundamental role in machine learning, data science, and
engineering. Testing convexity structure in nonlinear programs relies on verifying the …