A Perturbation Bound on the Subspace Estimator from Canonical Projections

Abstract

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.

To appear in Proc. of IEEE, ISIT 2022