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cs.IT2023
Fast and Low-Memory Compressive Sensing Algorithms for Low Tucker-Rank Tensor Approximation from Streamed Measurements
Cullen Haselby, Mark A. Iwen, Deanna Needell +2
In this paper we consider the problem of recovering a low-rank Tucker approximation to a massive tensor based solely on structured random compressive measurements. Crucially, the p…
cs.IT2023
On Graph Uncertainty Principle and Eigenvector Delocalization
Elizaveta Rebrova, Palina Salanevich
Uncertainty principles present an important theoretical tool in signal processing, as they provide limits on the time-frequency concentration of a signal. In many real-world applic…