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Asymptotic Risk of Overparameterized Likelihood Models: Double Descent Theory for Deep Neural Networks

28 February 2021

Papers citing "Asymptotic Risk of Overparameterized Likelihood Models: Double Descent Theory for Deep Neural Networks"

32 / 32 papers shown

Title
Benign overfitting in ridge regression Alexander Tsigler Peter L. Bartlett 84 169 0 29 Sep 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data Arthur Jacot Berfin cSimcsek Francesco Spadaro Clément Hongler Franck Gabriel 80 68 0 17 Jun 2020
$On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression$ On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression Denny Wu Ji Xu 75 123 0 10 Jun 2020
Triple descent and the two kinds of overfitting: Where & why do they appear? Stéphane dÁscoli Levent Sagun Giulio Biroli 77 80 0 05 Jun 2020
A Brief Prehistory of Double Descent Marco Loog T. Viering A. Mey Jesse H. Krijthe David Tax 61 69 0 07 Apr 2020
Regularization in High-Dimensional Regression and Classification via Random Matrix Theory Panagiotis Lolas 79 14 0 30 Mar 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 183 153 0 02 Mar 2020
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks Zitong Yang Yaodong Yu Chong You Jacob Steinhardt Yi-An Ma 76 186 0 26 Feb 2020
Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors Yehuda Dar Paul Mayer Lorenzo Luzi Richard G. Baraniuk 132 17 0 25 Feb 2020
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 74 83 0 19 Feb 2020
Analytic Study of Double Descent in Binary Classification: The Impact of Loss Ganesh Ramachandra Kini Christos Thrampoulidis 84 52 0 30 Jan 2020
Deep Double Descent: Where Bigger Models and More Data Hurt Preetum Nakkiran Gal Kaplun Yamini Bansal Tristan Yang Boaz Barak Ilya Sutskever 127 945 0 04 Dec 2019
A Model of Double Descent for High-dimensional Binary Linear Classification Zeyu Deng A. Kammoun Christos Thrampoulidis 105 148 0 13 Nov 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 113 639 0 14 Aug 2019
Benign Overfitting in Linear Regression Peter L. Bartlett Philip M. Long Gábor Lugosi Alexander Tsigler MLT 113 779 0 26 Jun 2019
Approximation and Non-parametric Estimation of ResNet-type Convolutional Neural Networks Kenta Oono Taiji Suzuki 112 58 0 24 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 244 747 0 19 Mar 2019
Two models of double descent for weak features M. Belkin Daniel J. Hsu Ji Xu 121 375 0 18 Mar 2019
Uniform convergence may be unable to explain generalization in deep learning Vaishnavh Nagarajan J. Zico Kolter MoMe AI4CE 92 317 0 13 Feb 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 254 1,660 0 28 Dec 2018
A jamming transition from under- to over-parametrization affects loss landscape and generalization S. Spigler Mario Geiger Stéphane dÁscoli Levent Sagun Giulio Biroli Matthieu Wyart 91 150 0 22 Oct 2018
Just Interpolate: Kernel "Ridgeless" Regression Can Generalize Tengyuan Liang Alexander Rakhlin 91 355 0 01 Aug 2018
Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization D. Kobak Jonathan Lomond Benoit Sanchez 79 89 0 28 May 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 293 3,489 0 09 Mar 2018
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 143 472 0 10 Oct 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 223 1,225 0 26 Jun 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 362 4,638 0 10 Nov 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,641 0 10 Dec 2015
High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification Yan Sun Stefan Wager 145 289 0 10 Jul 2015
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 292 591 0 27 Feb 2015
An Introduction to Matrix Concentration Inequalities J. Tropp 178 1,155 0 07 Jan 2015
High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing D. Donoho Andrea Montanari 243 223 0 28 Oct 2013