Think globally, fit locally under the Manifold Setup: Asymptotic
Analysis of Locally Linear Embedding

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Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding

12 March 2017

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Papers citing "Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding"

16 / 16 papers shown

Title
Kernel spectral joint embeddings for high-dimensional noisy datasets using duo-landmark integral operators Xiucai Ding Rong Ma 98 2 0 20 May 2024
Learning Low-Dimensional Nonlinear Structures from High-Dimensional Noisy Data: An Integral Operator Approach Xiucai Ding Rongkai Ma 95 9 0 28 Feb 2022
Inferring Manifolds From Noisy Data Using Gaussian Processes David B. Dunson Nan Wu 91 18 0 14 Oct 2021
Avoiding unwanted results in locally linear embedding: A new understanding of regularization Liren Lin 21 1 0 28 Aug 2021
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation Xiuyuan Cheng Nan Wu 122 29 0 25 Jan 2021
Locally Linear Embedding and its Variants: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 61 28 0 22 Nov 2020
Impact of signal-to-noise ratio and bandwidth on graph Laplacian spectrum from high-dimensional noisy point cloud Xiucai Ding Hau‐Tieng Wu 125 13 0 21 Nov 2020
Graph Based Gaussian Processes on Restricted Domains David B. Dunson Hau‐Tieng Wu Nan Wu GP 67 25 0 14 Oct 2020
Strong Uniform Consistency with Rates for Kernel Density Estimators with General Kernels on Manifolds Hau‐Tieng Wu Nan Wu 50 10 0 13 Jul 2020
Data-driven Efficient Solvers for Langevin Dynamics on Manifold in High Dimensions Yuan Gao Jiang Liu Nan Wu 54 12 0 22 May 2020
Scalability and robustness of spectral embedding: landmark diffusion is all you need Chao Shen Hau‐Tieng Wu 86 26 0 03 Jan 2020
$Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in $L^\infty$ from Random Samples$ Spectral Convergence of Graph Laplacian and Heat Kernel Reconstruction in $L^\infty$ from Random Samples David B. Dunson Hau‐Tieng Wu Nan Wu 114 65 0 11 Dec 2019
Geodesic Distance Estimation with Spherelets Didong Li David B. Dunson 71 23 0 29 Jun 2019
Optimal Recovery of Precision Matrix for Mahalanobis Distance from High Dimensional Noisy Observations in Manifold Learning M. Gavish Ronen Talmon P. Su Hau‐Tieng Wu 47 8 0 19 Apr 2019
When Locally Linear Embedding Hits Boundary Hau‐Tieng Wu Nan Wu 52 11 0 11 Nov 2018
Deep vs. Diverse Architectures for Classification Problems Colleen M. Farrelly 33 5 0 21 Aug 2017