Fast and Accurate Log-Determinant Approximations

Owen Deen; Colton River Waller; John P Ward

doi:10.1109/LSP.2024.3406481

Fast and Accurate Log-Determinant Approximations

Owen Deen
, Colton River Waller
, John P Ward

Research output: Contribution to journal › Article › peer-review

Abstract

We consider the problem of estimating log-determinants of large, sparse, positive definite matrices. A key focus of our algorithm is to reduce computational cost, and it is based on sparse approximate inverses. The algorithm can be implemented to be adaptive, and it uses graph spline approximation to improve accuracy. We illustrate our approach on classes of large sparse matrices.

Original language	English
Pages (from-to)	1520-1524
Number of pages	5
Journal	IEEE Signal Processing Letters
Volume	31
DOIs	https://doi.org/10.1109/LSP.2024.3406481
State	Published - Jan 1 2024

Keywords

Graph models
graph splines
log-determinant
positive definite
sparse matrices

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10.1109/LSP.2024.3406481

Cite this

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abstract = "We consider the problem of estimating log-determinants of large, sparse, positive definite matrices. A key focus of our algorithm is to reduce computational cost, and it is based on sparse approximate inverses. The algorithm can be implemented to be adaptive, and it uses graph spline approximation to improve accuracy. We illustrate our approach on classes of large sparse matrices.",

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AB - We consider the problem of estimating log-determinants of large, sparse, positive definite matrices. A key focus of our algorithm is to reduce computational cost, and it is based on sparse approximate inverses. The algorithm can be implemented to be adaptive, and it uses graph spline approximation to improve accuracy. We illustrate our approach on classes of large sparse matrices.

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KW - sparse matrices

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Fast and Accurate Log-Determinant Approximations

Abstract

Keywords

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