A survey of distributed optimization
In distributed optimization of multi-agent systems, agents cooperate to minimize a global
function which is a sum of local objective functions. Motivated by applications including …
function which is a sum of local objective functions. Motivated by applications including …
Balancing QoS and security in the edge: Existing practices, challenges, and 6G opportunities with machine learning
While the emerging 6G networks are anticipated to meet the high-end service quality
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
demands of the mobile edge users in terms of data rate and delay satisfaction, new attack …
Adaptation, learning, and optimization over networks
AH Sayed - Foundations and Trends® in Machine Learning, 2014 - nowpublishers.com
This work deals with the topic of information processing over graphs. The presentation is
largely self-contained and covers results that relate to the analysis and design of multi-agent …
largely self-contained and covers results that relate to the analysis and design of multi-agent …
Distributed continuous-time optimization: nonuniform gradient gains, finite-time convergence, and convex constraint set
In this paper, a distributed optimization problem with general differentiable convex objective
functions is studied for continuous-time multi-agent systems with single-integrator dynamics …
functions is studied for continuous-time multi-agent systems with single-integrator dynamics …
Multi-agent distributed optimization via inexact consensus ADMM
Multi-agent distributed consensus optimization problems arise in many signal processing
applications. Recently, the alternating direction method of multipliers (ADMM) has been …
applications. Recently, the alternating direction method of multipliers (ADMM) has been …
Distributed optimization for uncertain high-order nonlinear multiagent systems via dynamic gain approach
Q Ma, Q Meng, S Xu - IEEE Transactions on Systems, Man, and …, 2023 - ieeexplore.ieee.org
In this article, we investigate the distributed output optimization for general uncertain high-
order nonlinear multiagent systems (MASs), where nonlinear functions are constrained by a …
order nonlinear multiagent systems (MASs), where nonlinear functions are constrained by a …
On distributed convex optimization under inequality and equality constraints
M Zhu, S Martinez - IEEE Transactions on Automatic Control, 2011 - ieeexplore.ieee.org
We consider a general multi-agent convex optimization problem where the agents are to
collectively minimize a global objective function subject to a global inequality constraint, a …
collectively minimize a global objective function subject to a global inequality constraint, a …
Distributed continuous-time convex optimization with time-varying cost functions
In this paper, a time-varying distributed convex optimization problem is studied for
continuous-time multi-agent systems. The objective is to minimize the sum of local time …
continuous-time multi-agent systems. The objective is to minimize the sum of local time …
Diffusion strategies for adaptation and learning over networks: an examination of distributed strategies and network behavior
Nature provides splendid examples of real-time learning and adaptation behavior that
emerges from highly localized interactions among agents of limited capabilities. For …
emerges from highly localized interactions among agents of limited capabilities. For …
Distributed alternating direction method of multipliers
E Wei, A Ozdaglar - 2012 IEEE 51st IEEE Conference on …, 2012 - ieeexplore.ieee.org
We consider a network of agents that are cooperatively solving a global unconstrained
optimization problem, where the objective function is the sum of privately known local …
optimization problem, where the objective function is the sum of privately known local …