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A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion
Finite completability is the tipping point in LRMC, as a few additional samples of a finitely completable matrix guarantee its unique completability.
Deterministic Conditions for Subspace Identifiability from Incomplete Sampling
Consider a generic $r$-dimensional subspace of $\mathbb{R}^d$, $r<d$, and suppose that we are only given projections of this subspace onto small subsets of the canonical coordinates.
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