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Main Authors: Le, Quoc-Tung, Zheng, Léon, Riccietti, Elisa, Gribonval, Rémi
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2411.04506
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author Le, Quoc-Tung
Zheng, Léon
Riccietti, Elisa
Gribonval, Rémi
author_facet Le, Quoc-Tung
Zheng, Léon
Riccietti, Elisa
Gribonval, Rémi
contents In this paper, we investigate the butterfly factorization problem, i.e., the problem of approximating a matrix by a product of sparse and structured factors. We propose a new formal mathematical description of such factors, that encompasses many different variations of butterfly factorization with different choices of the prescribed sparsity patterns. Among these supports, we identify those that ensure that the factorization problem admits an optimum, thanks to a new property called ``chainability''. For those supports we propose a new butterfly algorithm that yields an approximate solution to the butterfly factorization problem and that is supported by stronger theoretical guarantees than existing factorization methods. Specifically, we show that the ratio of the approximation error by the minimum value is bounded by a constant, independent of the target matrix.
format Preprint
id arxiv_https___arxiv_org_abs_2411_04506
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Butterfly factorization with error guarantees
Le, Quoc-Tung
Zheng, Léon
Riccietti, Elisa
Gribonval, Rémi
Optimization and Control
In this paper, we investigate the butterfly factorization problem, i.e., the problem of approximating a matrix by a product of sparse and structured factors. We propose a new formal mathematical description of such factors, that encompasses many different variations of butterfly factorization with different choices of the prescribed sparsity patterns. Among these supports, we identify those that ensure that the factorization problem admits an optimum, thanks to a new property called ``chainability''. For those supports we propose a new butterfly algorithm that yields an approximate solution to the butterfly factorization problem and that is supported by stronger theoretical guarantees than existing factorization methods. Specifically, we show that the ratio of the approximation error by the minimum value is bounded by a constant, independent of the target matrix.
title Butterfly factorization with error guarantees
topic Optimization and Control
url https://arxiv.org/abs/2411.04506