OSLQ

Optimal Stochastic Krylov based Techniques for Large- Scale Log-Determinant Estimation

arXiv:2606.07004v1 Announce Type: new Abstract: Estimating the logarithm of the determinant of large sparse positive definite symmetric matrices is an important task in numerical linear algebra, machine learning, Gaussian processes, and uncertainty quantification. In this work, we introduce two scalable and efficient methods for large-scale log-determinant termed the Optimal Stochastic Arnoldi with Incomplete Orthogonalization Procedure (OSA-IOP) and the Optimal Stochastic Lanczos Quadrature...