A Perturbation Bound on the Subspace Estimator from Canonical Projections

Srivastava, Karan, Pimentel-Alarcón, Daniel L.

arXiv.org Machine Learning 

This paper derives a perturbation bound on the optimal subspace estimator obtained from a subset of its canonical projections contaminated by noise. This fundamental result has important implications in matrix completion, subspace clustering, and related problems.

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