Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon

28 December 2018

Papers citing "Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon"

28 / 28 papers shown

Title
Feature maps for the Laplacian kernel and its generalizations Sudhendu Ahir Parthe Pandit 101 0 0 24 Feb 2025
On the Pinsker bound of inner product kernel regression in large dimensions Weihao Lu Jialin Ding Haobo Zhang Qian Lin 93 1 0 02 Sep 2024
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning Fan He Mingzhe He Lei Shi Xiaolin Huang Johan A. K. Suykens 68 1 0 03 Jun 2024
Six Lectures on Linearized Neural Networks Theodor Misiakiewicz Andrea Montanari 141 13 0 25 Aug 2023
How many samples are needed to leverage smoothness? Vivien A. Cabannes Stefano Vigogna 62 2 0 25 May 2023
From Tempered to Benign Overfitting in ReLU Neural Networks Guy Kornowski Gilad Yehudai Ohad Shamir 91 13 0 24 May 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension Moritz Haas David Holzmüller U. V. Luxburg Ingo Steinwart MLT 102 14 0 23 May 2023
Kernel interpolation generalizes poorly Yicheng Li Haobo Zhang Qian Lin 73 11 0 28 Mar 2023
Strong inductive biases provably prevent harmless interpolation Michael Aerni Marco Milanta Konstantin Donhauser Fanny Yang 87 9 0 18 Jan 2023
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks Ilja Kuzborskij Csaba Szepesvári 75 4 0 28 Dec 2022
Rates of Convergence for Regression with the Graph Poly-Laplacian Nicolas García Trillos Ryan W. Murray Matthew Thorpe 93 5 0 06 Sep 2022
Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime Hong Hu Yue M. Lu 92 16 0 13 May 2022
Spectrum of inner-product kernel matrices in the polynomial regime and multiple descent phenomenon in kernel ridge regression Theodor Misiakiewicz 67 40 0 21 Apr 2022
Measuring Complexity of Learning Schemes Using Hessian-Schatten Total Variation Shayan Aziznejad Joaquim Campos M. Unser 93 10 0 12 Dec 2021
Harmless interpolation in regression and classification with structured features Andrew D. McRae Santhosh Karnik Mark A. Davenport Vidya Muthukumar 186 11 0 09 Nov 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 69 1 0 27 Sep 2021
Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping Ilja Kuzborskij Csaba Szepesvári 100 7 0 12 Jul 2021
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi Zhou Arthur Gretton MLT 105 35 0 06 Jun 2021
Fitting Elephants P. Mitra 26 0 0 31 Mar 2021
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman Chiyuan Zhang TDI 248 472 0 09 Aug 2020
Multiple Descent: Design Your Own Generalization Curve Lin Chen Yifei Min M. Belkin Amin Karbasi DRL 162 61 0 03 Aug 2020
Interpolation and Learning with Scale Dependent Kernels Nicolò Pagliana Alessandro Rudi Ernesto De Vito Lorenzo Rosasco 91 8 0 17 Jun 2020
Learning from Non-Random Data in Hilbert Spaces: An Optimal Recovery Perspective S. Foucart Chunyang Liao Shahin Shahrampour Yinsong Wang 43 0 0 05 Jun 2020
The Generalization Error of the Minimum-norm Solutions for Over-parameterized Neural Networks E. Weinan Chao Ma Lei Wu 57 14 0 15 Dec 2019
Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization T. Poggio Andrzej Banburski Q. Liao ODL 126 165 0 25 Aug 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 162 640 0 14 Aug 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 194 504 0 12 Jun 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 302 747 0 19 Mar 2019