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Improved spectral convergence rates for graph Laplacians on
  epsilon-graphs and k-NN graphs

Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs

29 October 2019
Jeff Calder
Nicolas García Trillos
ArXivPDFHTML

Papers citing "Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs"

5 / 5 papers shown
Title
Convolutional Filtering on Sampled Manifolds
Convolutional Filtering on Sampled Manifolds
Zhiyang Wang
Luana Ruiz
Alejandro Ribeiro
13
3
0
20 Nov 2022
A continuum limit for the PageRank algorithm
A continuum limit for the PageRank algorithm
Amber Yuan
Jeff Calder
Braxton Osting
15
18
0
24 Jan 2020
Scalability and robustness of spectral embedding: landmark diffusion is
  all you need
Scalability and robustness of spectral embedding: landmark diffusion is all you need
Chao Shen
Hau‐Tieng Wu
24
24
0
03 Jan 2020
Geometric structure of graph Laplacian embeddings
Geometric structure of graph Laplacian embeddings
Nicolas García Trillos
Franca Hoffmann
Bamdad Hosseini
14
23
0
30 Jan 2019
Nonparametric sparsity and regularization
Nonparametric sparsity and regularization
Lorenzo Rosasco
S. Villa
S. Mosci
M. Santoro
A. Verri
91
102
0
13 Aug 2012
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