Advances in wired and wireless technology have necessitated the development of theory,
models, and tools to cope with the new challenges posed by large-scale control and …

A new robust continuous-time optimization algorithm for distributed problems is presented
which guarantees fixed-time convergence. The algorithm is based on a Lyapunov function …

The problem of simultaneously learning several related tasks has received considerable
attention in several domains, especially in machine learning, with the so-called multitask …

The event-triggered scheduling of network transmissions has found many applications in
engineering tasks operated in cyber-physical systems for its competitive advantage of …

Integrated sensing and communication (ISAC) is emerged as a research hotspot of key
technologies in future wireless communication systems with the purpose of achieving …

The augmented Lagrangian method (ALM) is a classical optimization tool that solves a given
“difficult”(constrained) problem via finding solutions of a sequence of “easier”(often …

In this paper, the augmented Lagrange (AL) algorithm for distributed optimization is studied.
Compared with the existing results, this paper uses different techniques, including the …

In this paper, we study a special class of distributed convex optimization problems-
distributed parametric consensus optimization problem (DPCOP), for which a two-stage …

We consider distributed optimization problems where networked nodes cooperatively
minimize the sum of their locally known convex costs. A popular class of methods to solve …

In this work, we tackle the energy consumption problem of edge computing technology
looking at two key aspects:(i) reducing the energy burden of modern edge computing …