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Fixed-time Distributed Optimization under Time-Varying Communication Topology
TL;DR: In this paper, a nonlinear protocol for achieving distributed optimization for time-varying communication topology within a fixed time independent of the initial conditions is presented, where each agent in the network can access its private objective function, while exchange of local information is permitted between the neighbors.
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Abstract: This paper presents a method to solve distributed optimization problem within a fixed time over a time-varying communication topology. Each agent in the network can access its private objective function, while exchange of local information is permitted between the neighbors. This study investigates first nonlinear protocol for achieving distributed optimization for time-varying communication topology within a fixed time independent of the initial conditions. For the case when the global objective function is strictly convex, a second-order Hessian based approach is developed for achieving fixed-time convergence. In the special case of strongly convex global objective function, it is shown that the requirement to transmit Hessians can be relaxed and an equivalent first-order method is developed for achieving fixed-time convergence to global optimum. Results are further extended to the case where the underlying team objective function, possibly non-convex, satisfies only the Polyak-Łojasiewicz (PL) inequality, which is a relaxation of strong convexity.
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Citations
Cooperative fixed-time/finite-time distributed robust optimization of multi-agent systems
TL;DR: In this paper , a robust continuous-time optimization algorithm for distributed problems is presented which guarantees fixed-time convergence, based on a Lyapunov function technique and applied to a class of problems with coupled local cost functions.
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Distributed Support Vector Machines Over Dynamic Balanced Directed Networks
Mohammadreza Doostmohammadian,Alireza Aghasi,Themistoklis Charalambous,Usman A. Khan +3 more
- 01 Jan 2022
TL;DR: In this article, a continuous-time algorithm that incorporates network topology changes in discrete jumps is proposed to remove chattering that arises because of the discretization of the underlying CT process, which converges to the SVM classifier over time-varying weight balanced directed graphs by using arguments from matrix perturbation theory.
A Fixed-Time Convergent Distributed Algorithm for Strongly Convex Functions in a Time-Varying Network
Kunal Garg,Mayank Baranwal,Dimitra Panagou +2 more
- 14 Dec 2020
TL;DR: In this article, a distributed nonlinear protocol for minimizing the sum of convex objective functions in a fixed time under time-varying communication topology is presented, where each node in the network has access only to its private objective function, while exchange of local information, such as, state and gradient values, is permitted between the immediate neighbors.
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Time-varying multi-objective optimisation over switching graphs via fixed-time consensus algorithms
Zhongguo Li,Zhengtao Ding +1 more
TL;DR: This paper considers distributed multi-objective optimisation problems with time-varying cost functions for network-connected multi-agent systems over switching graphs with scalarisation approach to convert the problem into a weighted-sum objective.
Distributed delay-tolerant strategies for equality-constraint sum-preserving resource allocation
Mohammadreza Doostmohammadian,Alireza Aghasi,Maria Vrakopoulou,Hamid R. Rabiee,Usman A. Khan,Themistoklis Charalambous +5 more
- 27 Oct 2023
TL;DR: The findings show that convergence can be reached for general sign-preserving odd nonlinearity and delay-tolerant mechanisms to handle general bounded heterogeneous time-varying delays over the communication network of agents while preserving all-time feasibility are proposed.
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References
•Book
Graph Theoretic Methods in Multiagent Networks
Mehran Mesbahi,Magnus Egerstedt +1 more
- 25 Jun 2010
3.3K
Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs
TL;DR: This paper introduces a distributed algorithm, referred to as DIGing, based on a combination of a distributed inexact gradient method and a gradient tracking technique that converges to a global and consensual minimizer over time-varying graphs.
•Journal Article
A differential equation for modeling Nesterov's accelerated gradient method: theory and insights
TL;DR: A second-order ordinary differential equation is derived, which is the limit of Nesterov's accelerated gradient method, and it is shown that the continuous time ODE allows for a better understanding of Nestersov's scheme.
Distributed optimization in sensor networks
Michael G. Rabbat,Robert Nowak +1 more
- 26 Apr 2004
TL;DR: This paper investigates a general class of distributed algorithms for "in-network" data processing, eliminating the need to transmit raw data to a central point, and shows that for a broad class of estimation problems the distributed algorithms converge to within an /spl epsi/-ball around the globally optimal value.
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Hamed Karimi,Julie Nutini,Mark Schmidt +2 more
- 19 Sep 2016
TL;DR: Recently, this paper showed that the Polyak-Łojasiewicz PL inequality is actually weaker than the main conditions that have been explored to show linear convergence rates without strong convexity over the last 25 years.
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