Wasserstein approximation of measures via orthogonal frames: statistical and computational complexities
arXiv:2610.36581v1 Announce Type: cross Abstract: Dimension-reduction methods such as PCA identify a subspace capturing most of the variation in the data, but not a distinguished basis within it. Selecting a basis in which the samples are sparsely represented is a recurring task in unsupervised lea…
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- 2026-10-28 04:00 · arXiv stat.ML
Wasserstein approximation of measures via orthogonal frames: statistical and computational complexities