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Convergence of Graph Laplacian with kNN Self-tuned Kernels
v1v2 (latest)

Convergence of Graph Laplacian with kNN Self-tuned Kernels

3 November 2020
Xiuyuan Cheng
Hau‐Tieng Wu
ArXiv (abs)PDFHTML

Papers citing "Convergence of Graph Laplacian with kNN Self-tuned Kernels"

15 / 15 papers shown
Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
Dhruv Kohli
Sawyer Robertson
Gal Mishne
A. Cloninger
142
1
0
02 Oct 2025
Manifold learning in metric spaces
Manifold learning in metric spacesApplied and Computational Harmonic Analysis (ACHA), 2025
Liane Xu
Amit Singer
387
1
0
20 Mar 2025
Boundary Detection Algorithm Inspired by Locally Linear Embedding
Boundary Detection Algorithm Inspired by Locally Linear Embedding
Pei-Cheng Kuo
Nan Wu
356
0
0
26 Jun 2024
Conditional Generative Modeling for High-dimensional Marked Temporal Point Processes
Conditional Generative Modeling for High-dimensional Marked Temporal Point ProcessesKnowledge Discovery and Data Mining (KDD), 2023
Zheng Dong
Zekai Fan
Shixiang Zhu
DiffM
488
8
0
21 May 2023
Graph Laplacians on Shared Nearest Neighbor graphs and graph Laplacians
  on $k$-Nearest Neighbor graphs having the same limit
Graph Laplacians on Shared Nearest Neighbor graphs and graph Laplacians on kkk-Nearest Neighbor graphs having the same limit
A. Neuman
174
0
0
24 Feb 2023
Strong uniform convergence of Laplacians of random geometric and
  directed kNN graphs on compact manifolds
Strong uniform convergence of Laplacians of random geometric and directed kNN graphs on compact manifolds
Hélene Guérin
Dinh-Toan Nguyen
Viet Tran
260
2
0
20 Dec 2022
Bi-stochastically normalized graph Laplacian: convergence to manifold
  Laplacian and robustness to outlier noise
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noiseInformation and Inference A Journal of the IMA (JIII), 2022
Xiuyuan Cheng
Boris Landa
431
6
0
22 Jun 2022
The Manifold Scattering Transform for High-Dimensional Point Cloud Data
The Manifold Scattering Transform for High-Dimensional Point Cloud Data
Joyce A. Chew
H. Steach
Siddharth Viswanath
Hau‐Tieng Wu
M. Hirn
Deanna Needell
Smita Krishnaswamy
Michael Perlmutter
3DPC
305
15
0
21 Jun 2022
SpecNet2: Orthogonalization-free spectral embedding by neural networks
SpecNet2: Orthogonalization-free spectral embedding by neural networksMathematical and Scientific Machine Learning (MSML), 2022
Ziyu Chen
Yingzhou Li
Xiuyuan Cheng
218
7
0
14 Jun 2022
Spatiotemporal Analysis Using Riemannian Composition of Diffusion
  Operators
Spatiotemporal Analysis Using Riemannian Composition of Diffusion OperatorsApplied and Computational Harmonic Analysis (ACHA), 2022
Tal Shnitzer
Hau‐Tieng Wu
Ronen Talmon
194
11
0
21 Jan 2022
StreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm
StreaMRAK a Streaming Multi-Resolution Adaptive Kernel AlgorithmApplied Mathematics and Computation (Appl. Math. Comput.), 2021
Andreas Oslandsbotn
Ž. Kereta
Valeriya Naumova
Y. Freund
A. Cloninger
247
2
0
23 Aug 2021
Clustering dynamics on graphs: from spectral clustering to mean shift
  through Fokker-Planck interpolation
Clustering dynamics on graphs: from spectral clustering to mean shift through Fokker-Planck interpolation
Katy Craig
Nicolas García Trillos
D. Slepčev
249
6
0
18 Aug 2021
Kernel Two-Sample Tests for Manifold Data
Kernel Two-Sample Tests for Manifold Data
Xiuyuan Cheng
Yao Xie
364
12
0
07 May 2021
LDLE: Low Distortion Local Eigenmaps
LDLE: Low Distortion Local EigenmapsJournal of machine learning research (JMLR), 2021
Dhruv Kohli
A. Cloninger
Zhengchao Wan
421
23
0
26 Jan 2021
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolationApplied and Computational Harmonic Analysis (ACHA), 2021
Xiuyuan Cheng
Nan Wu
473
30
0
25 Jan 2021
1
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