Consistency of Lipschitz learning with infinite unlabeled data and finite labeled data

28 October 2017

Papers citing "Consistency of Lipschitz learning with infinite unlabeled data and finite labeled data"

11 / 11 papers shown

Title
$Computing Approximate $\ell_p$ Sensitivities$ Computing Approximate $\ell_p$ Sensitivities Swati Padmanabhan David P. Woodruff Qiuyi Zhang 53 0 0 07 Nov 2023
Consistency of Fractional Graph-Laplacian Regularization in Semi-Supervised Learning with Finite Labels Adrien Weihs Matthew Thorpe 8 2 0 14 Mar 2023
Large data limit of the MBO scheme for data clustering: convergence of the dynamics Tim Laux Jona Lelmi 37 7 0 13 Sep 2022
Rates of Convergence for Regression with the Graph Poly-Laplacian Nicolas García Trillos Ryan W. Murray Matthew Thorpe 32 4 0 06 Sep 2022
Lipschitz regularity of graph Laplacians on random data clouds Jeff Calder Nicolas García Trillos M. Lewicka 19 30 0 13 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs Siddhartha Mishra Roberto Molinaro PINN 25 171 0 29 Jun 2020
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates Jeff Calder Brendan Cook Matthew Thorpe D. Slepčev 24 82 0 19 Jun 2020
A continuum limit for the PageRank algorithm Amber Yuan Jeff Calder Braxton Osting 34 18 0 24 Jan 2020
Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs Jeff Calder Nicolas García Trillos 35 40 0 29 Oct 2019
Properly-weighted graph Laplacian for semi-supervised learning Jeff Calder D. Slepčev SSL 22 57 0 10 Oct 2018
Gromov-Hausdorff limit of Wasserstein spaces on point clouds Nicolás García Trillos 18 19 0 11 Feb 2017