9 citations · 13 across the 2 of their papers we have counts for
2 papers
math.NA2016★ 4 cited
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
David G. Anderson, Ming Gu
Low-rank matrix approximation is a fundamental tool in data analysis for processing large datasets, reducing noise, and finding important signals. In this work, we present a novel…
cs.DS2014★ 9 cited
An Efficient Algorithm for Unweighted Spectral Graph Sparsification
David G. Anderson, Ming Gu, Christopher Melgaard
Spectral graph sparsification has emerged as a powerful tool in the analysis of large-scale networks by reducing the overall number of edges, while maintaining a comparable graph L…