The Network Nullspace Property for Compressed Sensing of Big Data Over Networks

We present a novel condition, which we term the network nullspace property, which ensures accurate recovery of graph signals representing massive network-structured datasets from few signal values. The network nullspace property couples the cluster structure of the underlying network-structure with...

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Bibliographic Details
Published inFrontiers in applied mathematics and statistics Vol. 4
Main Authors Jung, Alexander, Hulsebos, Madelon
Format Journal Article
LanguageEnglish
Published Frontiers Media S.A 15.05.2018
Subjects
big data
complex networks
compressed sensing
convex optimization
semi-supervised learning
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Summary:We present a novel condition, which we term the network nullspace property, which ensures accurate recovery of graph signals representing massive network-structured datasets from few signal values. The network nullspace property couples the cluster structure of the underlying network-structure with the geometry of the sampling set. Our results can be used to design efficient sampling strategies based on the network topology.
ISSN:2297-4687
2297-4687
DOI:10.3389/fams.2018.00009