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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 training sample.
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R. A. Horn and C. R. Johnson · 2013
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Perfect clustering for stochastic blockmodel graphs via adjacency spectral embedding
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Limit theorems for eigenvectors of the normalized Laplacian for random graphs
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