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research article
Dynamic Average Diffusion With Randomized Coordinate Updates
December 1, 2019
This work derives and analyzes an online learning strategy for tracking the average of time-varying distributed signals by relying on randomized coordinate-descent updates. During each iteration, each agent selects or observes a random entry of the observation vector, and different agents may select different entries of their observations before engaging in a consultation step. Careful coordination of the interactions among agents is necessary to avoid bias and ensure convergence. We provide a convergence analysis for the proposed methods, and illustrate the results by means of simulations.
Use this identifier to reference this record
Type
research article
Web of Science ID
WOS:000492993200011
Authors
Publication date
2019-12-01
Volume
5
Issue
4
Start page
753
End page
767
Subjects
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
November 12, 2019