ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2312.15995
  4. Cited By
Generalization in Kernel Regression Under Realistic Assumptions

Generalization in Kernel Regression Under Realistic Assumptions

26 December 2023
Daniel Barzilai
Ohad Shamir
ArXivPDFHTML

Papers citing "Generalization in Kernel Regression Under Realistic Assumptions"

14 / 14 papers shown
Title
Benign Overfitting with Quantum Kernels
Benign Overfitting with Quantum Kernels
Joachim Tomasi
S. Anthoine
Hachem Kadri
42
0
0
21 Mar 2025
On the Saturation Effects of Spectral Algorithms in Large Dimensions
Weihao Lu
Haobo Zhang
Yicheng Li
Q. Lin
42
1
0
01 Mar 2025
Overfitting Regimes of Nadaraya-Watson Interpolators
Overfitting Regimes of Nadaraya-Watson Interpolators
Daniel Barzilai
Guy Kornowski
Ohad Shamir
76
0
0
11 Feb 2025
Generalization for Least Squares Regression With Simple Spiked
  Covariances
Generalization for Least Squares Regression With Simple Spiked Covariances
Jiping Li
Rishi Sonthalia
28
0
0
17 Oct 2024
Simple Relative Deviation Bounds for Covariance and Gram Matrices
Simple Relative Deviation Bounds for Covariance and Gram Matrices
Daniel Barzilai
Ohad Shamir
18
0
0
08 Oct 2024
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying
  Bandwidth or Dimensionality
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
Marko Medvedev
Gal Vardi
Nathan Srebro
68
3
0
05 Sep 2024
On the Pinsker bound of inner product kernel regression in large
  dimensions
On the Pinsker bound of inner product kernel regression in large dimensions
Weihao Lu
Jialin Ding
Haobo Zhang
Qian Lin
52
0
0
02 Sep 2024
Entrywise error bounds for low-rank approximations of kernel matrices
Entrywise error bounds for low-rank approximations of kernel matrices
Alexander Modell
59
0
0
23 May 2024
The phase diagram of kernel interpolation in large dimensions
The phase diagram of kernel interpolation in large dimensions
Haobo Zhang
Weihao Lu
Qian Lin
60
5
0
19 Apr 2024
Characterizing Overfitting in Kernel Ridgeless Regression Through the
  Eigenspectrum
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
Tin Sum Cheng
Aurelien Lucchi
Anastasis Kratsios
David Belius
37
8
0
02 Feb 2024
Controlling the Inductive Bias of Wide Neural Networks by Modifying the
  Kernel's Spectrum
Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum
Amnon Geifman
Daniel Barzilai
Ronen Basri
Meirav Galun
29
5
0
26 Jul 2023
Precise Learning Curves and Higher-Order Scaling Limits for Dot Product
  Kernel Regression
Precise Learning Curves and Higher-Order Scaling Limits for Dot Product Kernel Regression
Lechao Xiao
Hong Hu
Theodor Misiakiewicz
Yue M. Lu
Jeffrey Pennington
65
18
0
30 May 2022
The Eigenlearning Framework: A Conservation Law Perspective on Kernel
  Regression and Wide Neural Networks
The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks
James B. Simon
Madeline Dickens
Dhruva Karkada
M. DeWeese
48
27
0
08 Oct 2021
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural
  Networks
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon
Abdulkadir Canatar
C. Pehlevan
144
201
0
07 Feb 2020
1