Sep 21, 2022 · In this paper, we study the problem of recovering a low-rank matrix from a number of noisy random linear measurements.
This paper studies the problem of recovering a low-rank matrix from several noisy random linear measurements. We consider the setting where the rank of the ...
This paper proposes an efficient stopping strategy based on the common hold-out method and shows that it detects a nearly optimal estimator provably and can ...
A Validation Approach to Over-parameterized Matrix and ...
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In this paper, we study the problem of recovering a low-rank matrix from a number of noisy random linear measurements. We consider the setting where the ...
Oct 8, 2024 · This paper investigates the recovery of a low-rank matrix from noisy linear measurements when the rank of the ground-truth matrix is unknown ...
Oct 7, 2024 · This paper studies the problem of recovering a low-rank matrix from noisy random linear measurements. The researchers consider a setting ...
Co-authors ; A validation approach to over-parameterized matrix and image recovery. L Ding, Z Qin, L Jiang, J Zhou, Z Zhu. arXiv preprint arXiv:2209.10675, 2022.
This paper studies the problem of recovering a low-rank matrix from several noisy random linear measurements. We consider the setting where the rank of the ...
A validation approach to over-parameterized matrix and image recovery. L Ding, Z Qin, L Jiang, J Zhou, Z Zhu. arXiv preprint arXiv:2209.10675, 2022. 12, 2022.
In this paper, we study the problem of recovering a low-rank matrix from a number of noisy random linear measurements. We consider the setting where the ...