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20122023
most citedDistributed Algorithms for Computation of Centrality Measures in Complex Networks

84 citations · 558 across the 52 of their papers we have counts for

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Showing cs.DCShow all

6 papers · 1 filter

cs.DC2019★ 17 cited

Fully Asynchronous Distributed Optimization with Linear Convergence in Directed Networks

Jiaqi Zhang, Keyou You

We consider the distributed optimization problem, the goal of which is to minimize the sum of local objective functions over a directed network. Though it has been widely studied r…

cs.DC2018★ 73 cited

AsySPA: An Exact Asynchronous Algorithm for Convex Optimization Over Digraphs

Jiaqi Zhang, Keyou You

This paper proposes a novel exact distributed asynchronous subgradient-push algorithm (AsySPA) to solve an additive cost optimization problem over directed graphs where each node o…

cs.DC2017★ 1 cited

How to Stop Consensus Algorithms, locally?

Pei Xie, Keyou You, Cheng Wu

This paper studies problems on locally stopping distributed consensus algorithms over networks where each node updates its state by interacting with its neighbors and decides by it…

cs.DC2017★ 1 cited

Distributed Random-Fixed Projected Algorithm for Constrained Optimization Over Digraphs

Pei Xie, Keyou You, Shiji Song +1

This paper is concerned with a constrained optimization problem over a directed graph (digraph) of nodes, in which the cost function is a sum of local objectives, and each node onl…

cs.DC2016★ 3 cited

Distributed Convex Optimization with Inequality Constraints over Time-varying Unbalanced Digraphs

Pei Xie, Keyou You, Roberto Tempo +2

This paper considers a distributed convex optimization problem with inequality constraints over time-varying unbalanced digraphs, where the cost function is a sum of local objectiv…

cs.DC2016

Distributed Algorithms for Robust Convex Optimization via the Scenario Approach

Keyou You, Roberto Tempo, Pei Xie

This paper proposes distributed algorithms to solve robust convex optimization (RCO) when the constraints are affected by nonlinear uncertainty. We adopt a scenario approach by ran…