Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 54 tok/s
Gemini 2.5 Pro 50 tok/s Pro
GPT-5 Medium 18 tok/s Pro
GPT-5 High 31 tok/s Pro
GPT-4o 105 tok/s Pro
Kimi K2 182 tok/s Pro
GPT OSS 120B 466 tok/s Pro
Claude Sonnet 4 40 tok/s Pro
2000 character limit reached

Novel and refined stability estimates for kernel matrices (2409.04263v1)

Published 6 Sep 2024 in math.NA and cs.NA

Abstract: Kernel matrices are a key quantity within kernel based approximation, and important properties like stability or convergence of algorithms can be analyzed with help of it. In this work we refine a multivariate Ingham-type theorem, which is then leveraged to obtain novel and refined stability estimates on kernel matrices, focussing on the case of finitely smooth kernels. In particular we obtain results that relate the Rayleigh quotients of kernel matrices for kernels of different smoothness to each other. Finally we comment on conclusions for the eigenvectors of these kernel matrices.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.

Authors (2)

X Twitter Logo Streamline Icon: https://streamlinehq.com