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1911.05822
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A Model of Double Descent for High-dimensional Binary Linear Classification
13 November 2019
Zeyu Deng
A. Kammoun
Christos Thrampoulidis
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Papers citing
"A Model of Double Descent for High-dimensional Binary Linear Classification"
25 / 25 papers shown
Title
The Double Descent Behavior in Two Layer Neural Network for Binary Classification
Chathurika S Abeykoon
A. Beknazaryan
Hailin Sang
46
1
0
27 Apr 2025
Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets
Khen Cohen
Noam Levi
Yaron Oz
BDL
23
1
0
28 May 2024
Gibbs-Based Information Criteria and the Over-Parameterized Regime
Haobo Chen
Yuheng Bu
Greg Wornell
21
1
0
08 Jun 2023
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage
Yu Gui
Cong Ma
Yiqiao Zhong
17
6
0
06 Jun 2023
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
Kuo-Wei Lai
Vidya Muthukumar
18
5
0
13 Mar 2023
Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures
Antione Bodin
N. Macris
26
4
0
13 Dec 2022
Tight bounds for maximum
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\ell_1
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1
-margin classifiers
Stefan Stojanovic
Konstantin Donhauser
Fanny Yang
35
0
0
07 Dec 2022
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
Deep Linear Networks can Benignly Overfit when Shallow Ones Do
Niladri S. Chatterji
Philip M. Long
15
8
0
19 Sep 2022
Intersection of Parallels as an Early Stopping Criterion
Ali Vardasbi
Maarten de Rijke
Mostafa Dehghani
MoMe
28
5
0
19 Aug 2022
Differentially Private Regression with Unbounded Covariates
Jason Milionis
Alkis Kalavasis
Dimitris Fotakis
Stratis Ioannidis
23
10
0
19 Feb 2022
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model
A. Bodin
N. Macris
27
13
0
22 Oct 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning
Yehuda Dar
Vidya Muthukumar
Richard G. Baraniuk
24
71
0
06 Sep 2021
Interpolation can hurt robust generalization even when there is no noise
Konstantin Donhauser
Alexandru cTifrea
Michael Aerni
Reinhard Heckel
Fanny Yang
26
14
0
05 Aug 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting
Frederic Koehler
Lijia Zhou
Danica J. Sutherland
Nathan Srebro
19
55
0
17 Jun 2021
Double Descent and Other Interpolation Phenomena in GANs
Lorenzo Luzi
Yehuda Dar
Richard Baraniuk
10
5
0
07 Jun 2021
Towards an Understanding of Benign Overfitting in Neural Networks
Zhu Li
Zhi-Hua Zhou
A. Gretton
MLT
31
35
0
06 Jun 2021
AdaBoost and robust one-bit compressed sensing
Geoffrey Chinot
Felix Kuchelmeister
Matthias Löffler
Sara van de Geer
27
5
0
05 May 2021
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini
Orestis Paraskevas
Samet Oymak
Christos Thrampoulidis
24
93
0
02 Mar 2021
Precise Statistical Analysis of Classification Accuracies for Adversarial Training
Adel Javanmard
Mahdi Soltanolkotabi
AAML
26
62
0
21 Oct 2020
The Lasso with general Gaussian designs with applications to hypothesis testing
Michael Celentano
Andrea Montanari
Yuting Wei
42
63
0
27 Jul 2020
When Does Preconditioning Help or Hurt Generalization?
S. Amari
Jimmy Ba
Roger C. Grosse
Xuechen Li
Atsushi Nitanda
Taiji Suzuki
Denny Wu
Ji Xu
26
32
0
18 Jun 2020
Classification vs regression in overparameterized regimes: Does the loss function matter?
Vidya Muthukumar
Adhyyan Narang
Vignesh Subramanian
M. Belkin
Daniel J. Hsu
A. Sahai
30
148
0
16 May 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime
Stéphane dÁscoli
Maria Refinetti
Giulio Biroli
Florent Krzakala
88
152
0
02 Mar 2020
A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-
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\ell_1
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-Norm Interpolated Classifiers
Tengyuan Liang
Pragya Sur
25
68
0
05 Feb 2020
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