Introduces OSA-IOP and OSLQ as scalable stochastic Krylov methods for large-scale log-determinant estimation, with derived error bounds and numerical experiments on real-world matrices.
Novel technique based on l\’eja points approximation for log-determinant estimation of large matrices.arXiv preprint arXiv:2603.02207, 2026
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Optimal Stochastic Krylov based Techniques for Large- Scale Log-Determinant Estimation
Introduces OSA-IOP and OSLQ as scalable stochastic Krylov methods for large-scale log-determinant estimation, with derived error bounds and numerical experiments on real-world matrices.