Surprises in High-Dimensional Ridgeless Least Squares Interpolation

19 March 2019

Papers citing "Surprises in High-Dimensional Ridgeless Least Squares Interpolation"

43 / 143 papers shown

Title
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi-Hua Zhou A. Gretton MLT 33 35 0 06 Jun 2021
Fundamental tradeoffs between memorization and robustness in random features and neural tangent regimes Elvis Dohmatob 25 9 0 04 Jun 2021
AdaBoost and robust one-bit compressed sensing Geoffrey Chinot Felix Kuchelmeister Matthias Löffler Sara van de Geer 32 5 0 05 May 2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split Samet Oymak Mingchen Li Mahdi Soltanolkotabi AI4CE OOD 36 13 0 29 Apr 2021
The Shape of Learning Curves: a Review T. Viering Marco Loog 18 122 0 19 Mar 2021
Learning curves of generic features maps for realistic datasets with a teacher-student model Bruno Loureiro Cédric Gerbelot Hugo Cui Sebastian Goldt Florent Krzakala M. Mézard Lenka Zdeborová 30 135 0 16 Feb 2021
When and How Mixup Improves Calibration Linjun Zhang Zhun Deng Kenji Kawaguchi James Zou UQCV 28 67 0 11 Feb 2021
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks Xiangyu Chang Yingcong Li Samet Oymak Christos Thrampoulidis 35 50 0 16 Dec 2020
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition Ben Adlam Jeffrey Pennington UD 37 93 0 04 Nov 2020
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 36 238 0 30 Oct 2020
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers Fan Yang Hongyang R. Zhang Sen Wu Christopher Ré Weijie J. Su 58 10 0 22 Oct 2020
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard Mahdi Soltanolkotabi AAML 26 62 0 21 Oct 2020
On the proliferation of support vectors in high dimensions Daniel J. Hsu Vidya Muthukumar Ji Xu 24 42 0 22 Sep 2020
Multiple Descent: Design Your Own Generalization Curve Lin Chen Yifei Min M. Belkin Amin Karbasi DRL 23 61 0 03 Aug 2020
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training Andrea Montanari Yiqiao Zhong 47 95 0 25 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip H. S. Torr NoLa AAML 23 57 0 08 Jul 2020
Exploring Weight Importance and Hessian Bias in Model Pruning Mingchen Li Yahya Sattar Christos Thrampoulidis Samet Oymak 28 3 0 19 Jun 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 34 32 0 18 Jun 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton Michal Derezinski Feynman T. Liang Zhenyu A. Liao Michael W. Mahoney 32 23 0 18 Jun 2020
Interpolation and Learning with Scale Dependent Kernels Nicolò Pagliana Alessandro Rudi E. De Vito Lorenzo Rosasco 38 8 0 17 Jun 2020
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks Yehuda Dar Richard G. Baraniuk 36 19 0 12 Jun 2020
To Each Optimizer a Norm, To Each Norm its Generalization Sharan Vaswani Reza Babanezhad Jose Gallego Aaron Mishkin Simon Lacoste-Julien Nicolas Le Roux 26 8 0 11 Jun 2020
Double Descent Risk and Volume Saturation Effects: A Geometric Perspective Prasad Cheema M. Sugiyama 6 3 0 08 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks Z. Fan Zhichao Wang 44 71 0 25 May 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 41 148 0 16 May 2020
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 152 371 0 09 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 41 172 0 23 Apr 2020
Boolean learning under noise-perturbations in hardware neural networks Louis Andréoli X. Porte Stéphane Chrétien M. Jacquot L. Larger Daniel Brunner 15 12 0 27 Mar 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 93 152 0 02 Mar 2020
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang AAML 33 222 0 25 Feb 2020
Generalisation error in learning with random features and the hidden manifold model Federica Gerace Bruno Loureiro Florent Krzakala M. Mézard Lenka Zdeborová 25 165 0 21 Feb 2020
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 26 82 0 19 Feb 2020
Learning Not to Learn in the Presence of Noisy Labels Liu Ziyin Blair Chen Ru Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda NoLa 18 18 0 16 Feb 2020
Asymptotic errors for convex penalized linear regression beyond Gaussian matrices Cédric Gerbelot A. Abbara Florent Krzakala 31 16 0 11 Feb 2020
$A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-$\ell_1$-Norm Interpolated Classifiers$ A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum- $\ell_1$ -Norm Interpolated Classifiers Tengyuan Liang Pragya Sur 33 68 0 05 Feb 2020
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 21 77 0 10 Dec 2019
In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors Jeffrey Negrea Gintare Karolina Dziugaite Daniel M. Roy AI4CE 32 64 0 09 Dec 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 36 85 0 09 Oct 2019
Ridge Regression: Structure, Cross-Validation, and Sketching Sifan Liu Yan Sun CML 25 48 0 06 Oct 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 47 626 0 14 Aug 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 21 481 0 12 Jun 2019
Scaling description of generalization with number of parameters in deep learning Mario Geiger Arthur Jacot S. Spigler Franck Gabriel Levent Sagun Stéphane dÁscoli Giulio Biroli Clément Hongler M. Wyart 44 195 0 06 Jan 2019
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 52 464 0 10 Oct 2017