Algorithms have never been more important. As the recipes of computer programs,
algorithms rule our lives. Although they can be forces for both good and evil, this is not a …

The pressure of climate change has been driving the transition of power distribution
networks (PDNs) to low-carbon energy systems. Hydrogen-based microgrids (HMGs), as …

The primary goal in cluster analysis is to discover natural groupings of objects. The field of
cluster analysis is crowded with diverse methods that make special assumptions about data …

Proximal distance algorithms combine the classical penalty method of constrained
minimization with distance majorization. If f (x) is the loss function, and C is the constraint set …

Estimation in generalized linear models (GLM) is complicated by the presence of
constraints. One can handle constraints by maximizing a penalized log-likelihood. Penalties …

In convex optimization, there is an {\em acceleration} phenomenon in which we can boost
the convergence rate of certain gradient-based algorithms. We can observe this …

Active reconfigurable intelligent surface (RIS) is a new RIS architecture that can reflect and
amplify communication signals. It can provide enhanced performance gain compared to the …

The problem of finding a best approximation pair of two sets, which in turn generalizes the
well known convex feasibility problem, has a long history that dates back to work by Cheney …

In the pricing of customized products, it is challenging to accurately predict the purchase
likelihood of potential clients for each personalized request. The heterogeneity of customers …

This paper studies nonconvex quadratically constrained quadratic program (QCQP), which
is known to be NP-hard in general. In the past decades, various approximate approaches …