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Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree
v1v2 (latest)

Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree

2 February 2020
Peizhong Ju
Xiaojun Lin
Jia Liu
ArXiv (abs)PDFHTML

Papers citing "Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree"

6 / 6 papers shown
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized
  Linear Models
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear ModelsNeural Information Processing Systems (NeurIPS), 2022
Lijia Zhou
Frederic Koehler
Pragya Sur
Danica J. Sutherland
Nathan Srebro
394
12
0
21 Oct 2022
Optimistic Rates: A Unifying Theory for Interpolation Learning and
  Regularization in Linear Regression
Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression
Lijia Zhou
Frederic Koehler
Danica J. Sutherland
Nathan Srebro
322
28
0
08 Dec 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and
  Benign Overfitting
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting
Frederic Koehler
Lijia Zhou
Danica J. Sutherland
Nathan Srebro
379
62
0
17 Jun 2021
On the robustness of minimum norm interpolators and regularized
  empirical risk minimizers
On the robustness of minimum norm interpolators and regularized empirical risk minimizersAnnals of Statistics (Ann. Stat.), 2020
Geoffrey Chinot
Matthias Löffler
Sara van de Geer
445
21
0
01 Dec 2020
Dimensionality reduction, regularization, and generalization in
  overparameterized regressions
Dimensionality reduction, regularization, and generalization in overparameterized regressionsSIAM Journal on Mathematics of Data Science (SIMODS), 2020
Ningyuan Huang
D. Hogg
Soledad Villar
323
19
0
23 Nov 2020
On Uniform Convergence and Low-Norm Interpolation Learning
On Uniform Convergence and Low-Norm Interpolation LearningNeural Information Processing Systems (NeurIPS), 2020
Lijia Zhou
Danica J. Sutherland
Nathan Srebro
330
31
0
10 Jun 2020
1
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