Adversarial Robust Low Rank Matrix Estimation: Compressed Sensing and Matrix Completion

10/25/2020 ∙ by Takeyuki Sasai, et al. ∙ 0

We consider robust low rank matrix estimation when random noise is heavy-tailed and output is contaminated by adversarial noise. Under the clear conditions, we firstly attain a fast convergence rate for low rank matrix estimation including compressed sensing and matrix completion with convex estimators.

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