Two-way Spectrum Pursuit for CUR Decomposition and Its Application in Joint Column/Row Subset Selection
Abstract
The problem of simultaneous column and row subset selection is addressed in this paper. The column space and row space of a matrix are spanned by its left and right singular vectors, respectively. However, the singular vectors are not within actual columns/rows of the matrix. In this paper, an iterative approach is proposed to capture the most structural information of columns/rows via selecting a subset of actual columns/rows. This algorithm is referred to as two-way spectrum pursuit (TWSP) which provides us with an accurate solution for the CUR matrix decomposition. TWSP is applicable in a wide range of applications since it enjoys a linear complexity w.r.t. number of original columns/rows. We demonstrated the application of TWSP for joint channel and sensor selection in cognitive radio networks, informative users and contents detection, and efficient supervised data reduction.
Keywords
Cite
@article{arxiv.2106.06983,
title = {Two-way Spectrum Pursuit for CUR Decomposition and Its Application in Joint Column/Row Subset Selection},
author = {Ashkan Esmaeili and Mohsen Joneidi and Mehrdad Salimitari and Umar Khalid and Nazanin Rahnavard},
journal= {arXiv preprint arXiv:2106.06983},
year = {2021}
}