We consider the problem of decentralized consensus optimization, where the sum of n smooth and strongly convex functions are minimized over n distributed agents that form a …
We consider decentralized optimization problems in which a number of agents collaborate to minimize the average of their local functions by exchanging over an underlying …
X Cao, T Başar - IEEE Transactions on Signal Processing, 2020 - ieeexplore.ieee.org
Decentralized multi-agent optimization usually relies on information exchange between neighboring agents, which can incur unaffordable communication overhead in practice. To …
R Nassif, S Vlaski, M Carpentiero… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the …
We consider a multi-agent network where each node has a stochastic (local) cost function that depends on the decision variable of that node and a random variable, and further, the …
We study a distributed method called SAB-TV, which employs gradient tracking to collaboratively minimize the strongly-convex sum of smooth local cost functions for …
W Yan, X Cao - IEEE Transactions on Signal Processing, 2024 - ieeexplore.ieee.org
Decentralized optimization methods often entail information exchange between neighbors. Transmission failures can happen due to network congestion, hardware/software issues …
Y Li, Y Chen, Q Lü, S Deng, H Li - Journal of the Franklin Institute, 2023 - Elsevier
In this paper, we study the problem of decentralized optimization to minimize a finite sum of local convex cost functions over an undirected network. Compared with the existing works …
K Rajawat, C Kumar - arXiv preprint arXiv:2012.04402, 2020 - arxiv.org
We consider the decentralized convex optimization problem, where multiple agents must cooperatively minimize a cumulative objective function, with each local function expressible …