Vertex nomination, consistent estimation, and adversarial modification

DOI10.1214/20-EJS1744zbMath1448.62087arXiv1905.01776OpenAlexW3086536119MaRDI QIDQ2199707

Yanyan Li

Publication date: 14 September 2020

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1905.01776

zbMATH Keywords

networksrandom graphsstatisticsadversarial machine learningvertex nomination

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Applications of graph theory (05C90) Learning and adaptive systems in artificial intelligence (68T05) Probabilistic graphical models (62H22)

Related Items

Maximum A Posteriori Inference of Random Dot Product Graphs via Conic Programming ⋮ Vertex Nomination Between Graphs via Spectral Embedding and Quadratic Programming ⋮ Subgraph nomination: query by example subgraph retrieval in networks ⋮ Vertex nomination: the canonical sampling and the extended spectral nomination schemes

Uses Software

• mclust

Cites Work

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