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2002.01849
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iterative least squares: efficient recovery of ill-conditioned low rank matrices from few entries
SIAM Journal on Mathematics of Data Science (SIMODS), 2020
5 February 2020
Jonathan Bauch
B. Nadler
Pini Zilber
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Papers citing
"Rank $2r$ iterative least squares: efficient recovery of ill-conditioned low rank matrices from few entries"
12 / 12 papers shown
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Over-Parametrized Matrix Factorization in the Presence of Spurious Stationary Points
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Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
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Anru R. Zhang
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GNMR: A provable one-line algorithm for low rank matrix recovery
Pini Zilber
B. Nadler
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19
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A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples
International Conference on Machine Learning (ICML), 2021
C. Kümmerle
C. M. Verdun
202
25
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03 Jun 2021
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence
Journal of machine learning research (JMLR), 2021
Yuetian Luo
Anru R. Zhang
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24 Apr 2021
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence
Operational Research (OR), 2020
Yuetian Luo
Wen Huang
Xudong Li
Anru R. Zhang
494
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Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method
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213
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