1 citations · 2 across the 4 of their papers we have counts for
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stat.ML2018
Out-of-sample extension of graph adjacency spectral embedding
Keith Levin, Farbod Roosta-Khorasani, Michael W. Mahoney +1
Many popular dimensionality reduction procedures have out-of-sample extensions, which allow a practitioner to apply a learned embedding to observations not seen in the initial trai…
stat.ML2018
Vertex nomination: The canonical sampling and the extended spectral nomination schemes
Jordan Yoder, Li Chen, Henry Pao +5
Suppose that one particular block in a stochastic block model is of interest, but block labels are only observed for a few of the vertices in the network. Utilizing a graph realize…