Abstract: In this work, we focus on solving non-smooth non-convex maximization problems in multi-group multicast transmission. By leveraging Karush-Kuhn-Tucker (KKT) optimality conditions, we ...

Abstract: Metaheuristics are widely recognized gradient-free solvers to hard problems that do not meet the rigorous mathematical assumptions of conventional solvers. The automated design of ...

A new study reveals that dual-atom catalysts behave in a fundamentally different way than scientists previously thought, challenging a long-standing model used to predict catalytic performance.

The rapid commercialization of generative artificial intelligence (AI) has created business models that depend heavily on data rights, ...