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Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime

Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime

13 May 2022
Hong Hu
Yue M. Lu
ArXivPDFHTML

Papers citing "Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime"

15 / 15 papers shown
Title
On the Saturation Effects of Spectral Algorithms in Large Dimensions
Weihao Lu
Haobo Zhang
Yicheng Li
Q. Lin
34
1
0
01 Mar 2025
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
42
0
0
02 Sep 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
42
5
0
19 Apr 2024
Learning from higher-order statistics, efficiently: hypothesis tests,
  random features, and neural networks
Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks
Eszter Székely
Lorenzo Bardone
Federica Gerace
Sebastian Goldt
27
2
0
22 Dec 2023
Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem
Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem
Simon Segert
16
0
0
18 Nov 2023
Six Lectures on Linearized Neural Networks
Six Lectures on Linearized Neural Networks
Theodor Misiakiewicz
Andrea Montanari
29
12
0
25 Aug 2023
Asymptotics of Bayesian Uncertainty Estimation in Random Features
  Regression
Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression
You-Hyun Baek
S. Berchuck
Sayan Mukherjee
13
0
0
06 Jun 2023
Deterministic equivalent and error universality of deep random features
  learning
Deterministic equivalent and error universality of deep random features learning
Dominik Schröder
Hugo Cui
Daniil Dmitriev
Bruno Loureiro
MLT
14
28
0
01 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width
Bayes-optimal Learning of Deep Random Networks of Extensive-width
Hugo Cui
Florent Krzakala
Lenka Zdeborová
BDL
16
34
0
01 Feb 2023
Gradient flow in the gaussian covariate model: exact solution of
  learning curves and multiple descent structures
Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures
Antione Bodin
N. Macris
6
4
0
13 Dec 2022
Overparameterized random feature regression with nearly orthogonal data
Overparameterized random feature regression with nearly orthogonal data
Zhichao Wang
Yizhe Zhu
10
3
0
11 Nov 2022
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
48
18
0
30 May 2022
Eigenspace Restructuring: a Principle of Space and Frequency in Neural
  Networks
Eigenspace Restructuring: a Principle of Space and Frequency in Neural Networks
Lechao Xiao
13
21
0
10 Dec 2021
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy
  Regime
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime
Stéphane dÁscoli
Maria Refinetti
Giulio Biroli
Florent Krzakala
83
152
0
02 Mar 2020
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
131
199
0
07 Feb 2020
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