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math.NA2019
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery
Rachel Grotheer, Shuang Li, Anna Ma +2
Low-rank tensor recovery problems have been widely studied in many applications of signal processing and machine learning. Tucker decomposition is known as one of the most popular…
math.NA2019
Iterative Hard Thresholding for Low CP-rank Tensor Models
Rachel Grotheer, Shuang Li, Anna Ma +2
Recovery of low-rank matrices from a small number of linear measurements is now well-known to be possible under various model assumptions on the measurements. Such results demonstr…
math.NA2018
Alternatives for Generating a Reduced Basis to Solve the Hyperspectral Diffuse Optical Tomography Model
Rachel Grotheer, Thilo Strauss, Phil Gralla +1
The Reduced Basis Method (RBM) is a model reduction technique used to solve parametric PDEs that relies upon a basis set of solutions to the PDE at specific parameter values. To ge…