Blind Community Detection From Low-Rank Excitations of a Graph Filter

Volume: 68, Pages: 436 - 451
Published: Jan 1, 2020
Abstract
This paper considers a new framework to detect communities in a graph from the observation of signals at its nodes. We model the observed signals as noisy outputs of an unknown network process, represented as a graph filter that is excited by a set of unknown low-rank inputs/excitations. Application scenarios of this model include diffusion dynamics, pricing experiments, and opinion dynamics. Rather than learning the precise parameters of the...
Paper Details
Title
Blind Community Detection From Low-Rank Excitations of a Graph Filter
Published Date
Jan 1, 2020
Volume
68
Pages
436 - 451
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