学术科研-数学大讲堂

Guarantees of Riemannian Optimization for Low Rank Matrix Recovery

We establish theoretical recovery guarantees of a family of Riemannian optimization algorithms for low rank matrix recovery, which is about recovering an m×n rank r matrix from p<mn number of linear measurements. The algorithms are first interpreted as the iterative hard thresholding algorithms with subspace projections....