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1812.11167
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Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon
28 December 2018
Alexander Rakhlin
Xiyu Zhai
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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
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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
71
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
45
0
0
05 Jun 2020
The Generalization Error of the Minimum-norm Solutions for Over-parameterized Neural Networks
E. Weinan
Chao Ma
Lei Wu
59
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
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