Gradient-Based Spectral Embeddings of Random Dot Product Graphs
Marcelo Fiori, Bernardo Marenco, Federico Larroca, Paola Bermolen, Gonzalo Mateos
Paper
From BibTeX import
IEEE Transactions on Signal and Information Processing over Networks 10, pp. 1–16, 2024
Notes
Fiori and coauthors study Riemannian optimization on matrices with orthogonal columns, which we read in riva2026random as a gauge-fixing section of our principal bundle; their tangent-space dimension nd - d(d-1)/2 matches ours by complementary constraint counting.
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