Out-of-sample extension of graph adjacency spectral embedding

By Keith D. Levin, Farbod Roosta-Khorasani, Michael W. Mahoney, Carey E. Priebe. 2018

Subfields: Statistics and Probability, Graph Learning, Network Science & Complex Systems

How researchers see this paper

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In Statistics and Probability

1. Hayden S. Helm
2. Carey E. Priebe
3. Youngser Park
4. Brandon Duderstadt
5. Weiwei Yang

Citations in the corpus

• Tracking the perspectives of interacting language models (2024, methodology): “The methodology can be extended to instances where only a partial history of the sys-tem is observed via out-of-sample methods (Bengio et al., 2003; Levin et al., 2018).”
• Mental State Classification Using Multi-Graph Features (2022, background): “To overcome this problem, “out-of-sample" extensions of popular transductive embedding methods have been proposed to map new data to the space spanned by the original embeddings [11, 21, 22, 23].”