Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence

Author:

Charisopoulos Vasileios,Chen Yudong,Davis Damek,Díaz Mateo,Ding Lijun,Drusvyatskiy Dmitriy

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Analysis

Reference81 articles.

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3. Balcan, M.F., Liang, Y., Song, Z., Woodruff, D.P., Zhang, H.: Non-convex matrix completion and related problems via strong duality. Journal of Machine Learning Research 20(102), 1–56 (2019)

4. Bauch, J., Nadler, B.: Rank $$2r$$ iterative least squares: efficient recovery of ill-conditioned low rank matrices from few entries. arXiv preprint arXiv:2002.01849 (2020)

5. Bhojanapalli, S., Neyshabur, B., Srebro, N.: Global optimality of local search for low rank matrix recovery. In: Advances in Neural Information Processing Systems, pp. 3873–3881 (2016)

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