Riemannian thresholding methods for row-sparse and low-rank matrix recovery

Eisenmann, Henrik; Krahmer, Felix; Pfeffer, Max; Uschmajew, André

doi:10.1007/s11075-022-01433-5

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Riemannian thresholding methods for row-sparse and low-rank matrix recovery

Eisenmann, H., Krahmer, F., Pfeffer, M., & Uschmajew, A. (2023). Riemannian thresholding methods for row-sparse and low-rank matrix recovery. Numerical algorithms, 93(2), 669-693. doi:10.1007/s11075-022-01433-5.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-9ABB-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000D-9ABC-2

Genre: Journal Article

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Creators:
Eisenmann, Henrik¹, Author
Krahmer, Felix¹, Author
Pfeffer, Max¹, Author
Uschmajew, André¹, Author

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1Max Planck Institute for Mathematics in the Sciences, Max Planck Society, ou_3039308

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Dates: Date issued: 2023

Publication Status: Issued

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Identifiers: DOI: 10.1007/s11075-022-01433-5
Other: 88525

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Title: Numerical algorithms

Source Genre: Journal

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Pages: - Volume / Issue: 93 (2) Sequence Number: - Start / End Page: 669 - 693 Identifier: ISSN: 1572-9265