# Parallel MMF: a Multiresolution Approach to Matrix Computation

arXiv: https://arxiv.org/abs/1507.04396 · HTML: https://mlsanity.com/paper/1507.04396/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jul 2015.

## Built on by (most cited first, 1 of 1)

- [Fast Temporal Wavelet Graph Neural Networks](https://mlsanity.com/paper/2302.08643/) (2023)

## Abstract (arXiv)

Multiresolution Matrix Factorization (MMF) was recently introduced as a method for finding multiscale structure and defining wavelets on graphs/matrices. In this paper we derive pMMF, a parallel algorithm for computing the MMF factorization. Empirically, the running time of pMMF scales linearly in the dimension for sparse matrices. We argue that this makes pMMF a valuable new computational primitive in its own right, and present experiments on using pMMF for two distinct purposes: compressing matrices and preconditioning large sparse linear systems.