AI & ML
A simple stability analysis of the Lanczos algorithm in finite precision arithmetic
arXiv cs.NA0 views
arXiv:2608.21268v2 Announce Type: replace Abstract: We give a self-contained analysis of the symmetric Lanczos algorithm without reorthogonalization when computations are performed inexactly. We show the computed Lanczos vectors are well-behaved locally. From this we (i) prove Paige's loss-of-orthogonality identity, and (ii) construct a Greenbaum-type backward stability result, exhibiting a nearby problem on which exact Lanczos produces the computed tridiagonal matrix. This allows us to derive several facts about the computed Ritz values at the original eigenvalues. Our analysis simplifies the analyses of Paige and Greenbaum, at the cost of hiding polynomial factors in the iteration count.
Source:https://arxiv.org/abs/2608.21268PreviousAdvanced Linear Algebra with Applications - Part I (Numerical linear algebra for PDEs, machine learning, and data assimilation)NextSolving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach
Related posts
Heated mirror reveals hidden 3D patterns in rising air near a wall
0Phys.org Tech
Infrared-transparent aerogel boosts performance of subambient daytime radiative cooling materials by up to 5.2°C
0Phys.org Tech
Tracing the online networks behind AI-generated nude images
0Phys.org Tech
Microsoft's AI Risk Report Misses This Key Detail
0Dark Reading
Introducing the Grid Protectors Program
0OpenAI Blog
The world has a new plan to save nature, but it still needs the money
0Ars Technica