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math.NA2021
Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery
Mark A. Iwen, Deanna Needell, Michael Perlmutter +1
Recovery of sparse vectors and low-rank matrices from a small number of linear measurements is well-known to be possible under various model assumptions on the measurements. The ke…
math.NA2019
Sketching for Motzkin's Iterative Method for Linear Systems
Elizaveta Rebrova, Deanna Needell
Projection-based iterative methods for solving large over-determined linear systems are well-known for their simplicity and computational efficiency. It is also known that the corr…
math.NA2019
A Parallel Hierarchical Blocked Adaptive Cross Approximation Algorithm
Yang Liu, Wissam Sid-Lakhdar, Elizaveta Rebrova +2
This paper presents a hierarchical low-rank decomposition algorithm assuming any matrix element can be computed in time. The proposed algorithm computes rank-revealing decom…