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Fast Rates for Noisy Interpolation Require Rethinking the Effects of Inductive Bias

7 March 2022

Papers citing "Fast Rates for Noisy Interpolation Require Rethinking the Effects of Inductive Bias"

30 / 30 papers shown

Title
Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression Lijia Zhou Frederic Koehler Danica J. Sutherland Nathan Srebro 123 25 0 08 Dec 2021
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz Song Mei MLT 67 29 0 16 Nov 2021
Tight bounds for minimum l1-norm interpolation of noisy data Guillaume Wang Konstantin Donhauser Fanny Yang 109 20 0 10 Nov 2021
Foolish Crowds Support Benign Overfitting Niladri S. Chatterji Philip M. Long 125 20 0 06 Oct 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting Frederic Koehler Lijia Zhou Danica J. Sutherland Nathan Srebro 68 56 0 17 Jun 2021
AdaBoost and robust one-bit compressed sensing Geoffrey Chinot Felix Kuchelmeister Matthias Löffler Sara van de Geer 71 5 0 05 May 2021
On the robustness of minimum norm interpolators and regularized empirical risk minimizers Geoffrey Chinot Matthias Löffler Sara van de Geer 62 20 0 01 Dec 2020
Benign overfitting in ridge regression Alexander Tsigler Peter L. Bartlett 75 167 0 29 Sep 2020
Finite Versus Infinite Neural Networks: an Empirical Study Jaehoon Lee S. Schoenholz Jeffrey Pennington Ben Adlam Lechao Xiao Roman Novak Jascha Narain Sohl-Dickstein 77 214 0 31 Jul 2020
On Uniform Convergence and Low-Norm Interpolation Learning Lijia Zhou Danica J. Sutherland Nathan Srebro 59 29 0 10 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 92 151 0 16 May 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 124 339 0 11 Feb 2020
Neural Tangents: Fast and Easy Infinite Neural Networks in Python Roman Novak Lechao Xiao Jiri Hron Jaehoon Lee Alexander A. Alemi Jascha Narain Sohl-Dickstein S. Schoenholz 76 229 0 05 Dec 2019
A Model of Double Descent for High-dimensional Binary Linear Classification Zeyu Deng A. Kammoun Christos Thrampoulidis 85 146 0 13 Nov 2019
Benign Overfitting in Linear Regression Peter L. Bartlett Philip M. Long Gábor Lugosi Alexander Tsigler MLT 86 778 0 26 Jun 2019
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 87 336 0 13 Jun 2019
On Exact Computation with an Infinitely Wide Neural Net Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang 226 925 0 26 Apr 2019
Harmless interpolation of noisy data in regression Vidya Muthukumar Kailas Vodrahalli Vignesh Subramanian A. Sahai 80 202 0 21 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 194 743 0 19 Mar 2019
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 269 3,213 0 20 Jun 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 158 921 0 27 Oct 2017
High-dimensional classification by sparse logistic regression F. Abramovich V. Grinshtein 33 56 0 26 Jun 2017
Regularization and the small-ball method II: complexity dependent error rates Guillaume Lecué S. Mendelson 65 39 0 27 Aug 2016
High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification Yan Sun Stefan Wager 108 287 0 10 Jul 2015
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 184 706 0 30 Dec 2014
Learning without Concentration S. Mendelson 224 334 0 01 Jan 2014
Concentration inequalities for order statistics S. Boucheron Maud Thomas 156 81 0 31 Jul 2012
Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach Y. Plan Roman Vershynin 242 457 0 06 Feb 2012
$Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls$ Minimax rates of estimation for high-dimensional linear regression over $\ell_q$ -balls Garvesh Raskutti Martin J. Wainwright Bin Yu 220 575 0 11 Oct 2009
High-dimensional generalized linear models and the lasso Sara van de Geer 629 756 0 04 Apr 2008