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Multiple Descent: Design Your Own Generalization Curve

Multiple Descent: Design Your Own Generalization Curve

3 August 2020
Lin Chen
Yifei Min
M. Belkin
Amin Karbasi
    DRL
ArXivPDFHTML

Papers citing "Multiple Descent: Design Your Own Generalization Curve"

13 / 13 papers shown
Title
A dynamic view of the double descent
A dynamic view of the double descent
Vivek Shripad Borkar
63
0
0
03 May 2025
Investigating the Impact of Model Complexity in Large Language Models
Investigating the Impact of Model Complexity in Large Language Models
Jing Luo
Huiyuan Wang
Weiran Huang
34
0
0
01 Oct 2024
Extrapolated cross-validation for randomized ensembles
Extrapolated cross-validation for randomized ensembles
Jin-Hong Du
Pratik V. Patil
Kathryn Roeder
Arun K. Kuchibhotla
11
5
0
27 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
34
4
0
13 Dec 2022
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized
  Linear Models
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Lijia Zhou
Frederic Koehler
Pragya Sur
Danica J. Sutherland
Nathan Srebro
83
9
0
21 Oct 2022
Second-order regression models exhibit progressive sharpening to the
  edge of stability
Second-order regression models exhibit progressive sharpening to the edge of stability
Atish Agarwala
Fabian Pedregosa
Jeffrey Pennington
25
26
0
10 Oct 2022
The BUTTER Zone: An Empirical Study of Training Dynamics in Fully
  Connected Neural Networks
The BUTTER Zone: An Empirical Study of Training Dynamics in Fully Connected Neural Networks
Charles Edison Tripp
J. Perr-Sauer
L. Hayne
M. Lunacek
Jamil Gafur
AI4CE
21
0
0
25 Jul 2022
Multi-scale Feature Learning Dynamics: Insights for Double Descent
Multi-scale Feature Learning Dynamics: Insights for Double Descent
Mohammad Pezeshki
Amartya Mitra
Yoshua Bengio
Guillaume Lajoie
61
25
0
06 Dec 2021
Exponential Bellman Equation and Improved Regret Bounds for
  Risk-Sensitive Reinforcement Learning
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning
Yingjie Fei
Zhuoran Yang
Yudong Chen
Zhaoran Wang
39
46
0
06 Nov 2021
Towards an Understanding of Benign Overfitting in Neural Networks
Towards an Understanding of Benign Overfitting in Neural Networks
Zhu Li
Zhi-Hua Zhou
A. Gretton
MLT
33
35
0
06 Jun 2021
The Shape of Learning Curves: a Review
The Shape of Learning Curves: a Review
T. Viering
Marco Loog
18
122
0
19 Mar 2021
Random Features for Kernel Approximation: A Survey on Algorithms,
  Theory, and Beyond
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond
Fanghui Liu
Xiaolin Huang
Yudong Chen
Johan A. K. Suykens
BDL
39
172
0
23 Apr 2020
The Curious Case of Adversarially Robust Models: More Data Can Help,
  Double Descend, or Hurt Generalization
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization
Yifei Min
Lin Chen
Amin Karbasi
AAML
31
69
0
25 Feb 2020
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