General
Large Growth Happens: Gaussian Elimination with Partial Pivoting on Random Matrices
arXiv cs.NA0 views
arXiv:2610.08701v1 Announce Type: new Abstract: We prove that the probability that Gaussian elimination with partial pivoting on $n \times n$ random matrices has growth $\rho$ is at least inverse quasi-polynomial: $\Omega(\exp(-c \log^2 (\rho)\log(n)))$ for some constant $c > 0$. This lower bound breaks standard conjectures in the smoothed and average-case analysis of Gaussian elimination. To the best of our knowledge, it is the first non-trivial lower bound on the probability of large growth for Gaussian random matrices.
Source:https://arxiv.org/abs/2610.08701PreviousEffective computation of Moore-Penrose inverses over fields of rational functions by specializationsNextWell-posed by Design: Learning Constitutive Laws from Velocity Data using Convex Neural Network Potentials
Related posts
Vellinko – Sign PDFs in the browser without uploading them
0Hacker News New
Show HN: Vivio House, an interactive 3D headquarters
0Hacker News New
Pushover – Simple Notifications
0Hacker News New
The Gift of It's Your Problem Now (2021)
0Hacker News New
Implied News: News X Prediction Markets
0Hacker News New
Show HN: OpenDocBot - bring your own model to Word, Excel and PowerPoint
0Hacker News New