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2012.00807
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On the robustness of minimum norm interpolators and regularized empirical risk minimizers
Annals of Statistics (Ann. Stat.), 2020
1 December 2020
Geoffrey Chinot
Matthias Löffler
Sara van de Geer
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Papers citing
"On the robustness of minimum norm interpolators and regularized empirical risk minimizers"
14 / 14 papers shown
Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
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Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors
International Conference on Learning Representations (ICLR), 2023
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Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression
International Conference on Machine Learning (ICML), 2023
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Rong Ge
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01 Feb 2023
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Neural Information Processing Systems (NeurIPS), 2022
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Frederic Koehler
Pragya Sur
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21 Oct 2022
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
International Conference on Learning Representations (ICLR), 2022
Zong-xiao Li
Chong You
Srinadh Bhojanapalli
Daliang Li
A. S. Rawat
...
Kenneth Q Ye
Felix Chern
Felix X. Yu
Ruiqi Guo
Surinder Kumar
MoE
318
134
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12 Oct 2022
Deep Linear Networks can Benignly Overfit when Shallow Ones Do
Journal of machine learning research (JMLR), 2022
Niladri S. Chatterji
Philip M. Long
278
11
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19 Sep 2022
Fast Rates for Noisy Interpolation Require Rethinking the Effects of Inductive Bias
International Conference on Machine Learning (ICML), 2022
Konstantin Donhauser
Nicolò Ruggeri
Stefan Stojanovic
Fanny Yang
347
25
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07 Mar 2022
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data
Annual Conference Computational Learning Theory (COLT), 2022
Spencer Frei
Niladri S. Chatterji
Peter L. Bartlett
MLT
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11 Feb 2022
Tight bounds for minimum l1-norm interpolation of noisy data
Guillaume Wang
Konstantin Donhauser
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352
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10 Nov 2021
Foolish Crowds Support Benign Overfitting
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Philip M. Long
348
24
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06 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
314
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06 Sep 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting
Frederic Koehler
Lijia Zhou
Danica J. Sutherland
Nathan Srebro
373
62
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17 Jun 2021
Nonasymptotic theory for two-layer neural networks: Beyond the bias-variance trade-off
Huiyuan Wang
Wei Lin
MLT
251
5
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09 Jun 2021
AdaBoost and robust one-bit compressed sensing
Mathematical Statistics and Learning (MSL), 2021
Geoffrey Chinot
Felix Kuchelmeister
Matthias Löffler
Sara van de Geer
527
7
0
05 May 2021
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