Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise

31 May 2020

Papers citing "Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise"

20 / 20 papers shown

Title
Improving Deep Regression with Tightness Shihao Zhang Yuguang Yan Angela Yao OOD 84 0 0 13 Feb 2025
Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets Boris Landa Y. Kluger Rong Ma 27 0 0 01 Jul 2024
Sketching the Heat Kernel: Using Gaussian Processes to Embed Data Anna C. Gilbert Kevin OÑeill 27 0 0 01 Mar 2024
A cutting plane algorithm for globally solving low dimensional k-means clustering problems M. Ryner Jan Kronqvist Johan Karlsson 21 0 0 21 Feb 2024
Regularised optimal self-transport is approximate Gaussian mixture maximum likelihood Gilles Mordant OT 16 2 0 23 Oct 2023
Optimal Transport with Adaptive Regularisation Hugues van Assel Titouan Vayer Rémi Flamary Nicolas Courty OT 27 2 0 04 Oct 2023
Manifold Learning with Sparse Regularised Optimal Transport Stephen X. Zhang Gilles Mordant Tetsuya Matsumoto Geoffrey Schiebinger OT 29 11 0 19 Jul 2023
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities Hugues van Assel Titouan Vayer Rémi Flamary Nicolas Courty 25 9 0 23 May 2023
Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling Boris Landa Xiuyuan Cheng 36 6 0 16 Sep 2022
Beyond kNN: Adaptive, Sparse Neighborhood Graphs via Optimal Transport Tetsuya Matsumoto Stephen X. Zhang Geoffrey Schiebinger 24 5 0 01 Aug 2022
Orthogonalization of data via Gromov-Wasserstein type feedback for clustering and visualization M. Ryner Johan Karlsson DiffM 11 0 0 25 Jul 2022
ManiFeSt: Manifold-based Feature Selection for Small Data Sets David Cohen Tal Shnitzer Y. Kluger Ronen Talmon 17 2 0 18 Jul 2022
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise Xiuyuan Cheng Boris Landa 33 3 0 22 Jun 2022
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation Xiuyuan Cheng Nan Wu 63 29 0 25 Jan 2021
Doubly Stochastic Subspace Clustering Derek Lim René Vidal B. Haeffele 13 17 0 30 Nov 2020
Local Two-Sample Testing over Graphs and Point-Clouds by Random-Walk Distributions Boris Landa Rihao Qu Joseph T. Chang Y. Kluger 12 4 0 06 Nov 2020
A low discrepancy sequence on graphs A. Cloninger H. Mhaskar 37 3 0 08 Oct 2020
Spectral convergence of diffusion maps: improved error bounds and an alternative normalisation Caroline L. Wormell Sebastian Reich 10 37 0 03 Jun 2020
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 261 3,243 0 24 Nov 2016
Poisson noise reduction with non-local PCA Joseph Salmon Zachary T. Harmany Charles-Alban Deledalle Rebecca Willett 60 313 0 02 Jun 2012