ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2212.10287
106
2

Strong uniform convergence of Laplacians of random geometric and directed kNN graphs on compact manifolds

20 December 2022
Hélene Guérin
Dinh-Toan Nguyen
Viet Tran
ArXivPDFHTML
Abstract

Consider nnn points independently sampled from a density ppp of class C2\mathcal{C}^2C2 on a smooth compact ddd-dimensional sub-manifold M\mathcal{M}M of Rm\mathbb{R}^mRm, and consider the generator of a random walk visiting these points according to a transition kernel KKK. We study the almost sure uniform convergence of this operator to the diffusive Laplace-Beltrami operator when nnn tends to infinity. This work extends known results of the past 15 years. In particular, our result does not require the kernel KKK to be continuous, which covers the cases of walks exploring kkkNN-random and geometric graphs, and convergence rates are given. The distance between the random walk generator and the limiting operator is separated into several terms: a statistical term, related to the law of large numbers, is treated with concentration tools and an approximation term that we control with tools from differential geometry. The convergence of kkkNN Laplacians is detailed.

View on arXiv
Comments on this paper