Title
Least Squares Approximation via Sparse Subsampled Randomized Hadamard Transform
Abstract
Solving least squares (LS) problems is a major topic in many applications. With recent data explosion, traditional approach is no longer suitable while working with large datasets, instead, randomized algorithms become popular in addressing this issue. In this article we propose a new randomized algorithm - sparse subsampled randomized Hadamard transform (SpSRHT) for solving overdetermined least s...
Year
DOI
Venue
2022
10.1109/TBDATA.2020.2972887
IEEE Transactions on Big Data
Keywords
DocType
Volume
Transforms,Iterative methods,Big Data,Probability distribution,Guidelines,Least squares approximations,Explosions
Journal
8
Issue
ISSN
Citations 
2
2332-7790
0
PageRank 
References 
Authors
0.34
19
4
Name
Order
Citations
PageRank
Dan Teng101.01
Xiaowei Zhang261.47
Li Cheng351833.34
Delin Chu434035.76