Web: http://arxiv.org/abs/2201.11222

Jan. 28, 2022, 2:11 a.m. | Bernardo Marenco, Paola Bermolen, Marcelo Fiori, Federico Larroca, Gonzalo Mateos

cs.LG updates on arXiv.org arxiv.org

Given a sequence of random (directed and weighted) graphs, we address the
problem of online monitoring and detection of changes in the underlying data
distribution. Our idea is to endow sequential change-point detection (CPD)
techniques with a graph representation learning substrate based on the
versatile Random Dot Product Graph (RDPG) model. We consider efficient, online
updates of a judicious monitoring function, which quantifies the discrepancy
between the streaming graph observations and the nominal RDPG. This reference
distribution is inferred via …

arxiv change detection graphs online product random

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