3 papers
math.NA2020
A Novel Regularization Based on the Error Function for Sparse Recovery
Weihong Guo, Yifei Lou, Jing Qin +1
Regularization plays an important role in solving ill-posed problems by adding extra information about the desired solution, such as sparsity. Many regularization terms usually inv…
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…