Surprises in High-Dimensional Ridgeless Least Squares Interpolation

19 March 2019

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

50 / 139 papers shown

Title
Demystifying Disagreement-on-the-Line in High Dimensions Dong-Hwan Lee Behrad Moniri Xinmeng Huang Yan Sun Hamed Hassani 21 8 0 31 Jan 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 16 0 0 26 Jan 2023
Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures Antione Bodin N. Macris 34 4 0 13 Dec 2022
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization Jiahui Cheng Minshuo Chen Hao Liu Tuo Zhao Wenjing Liao 36 0 0 01 Dec 2022
A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance Marco Loog T. Viering 23 1 0 25 Nov 2022
A Consistent Estimator for Confounding Strength Luca Rendsburg L. C. Vankadara D. Ghoshdastidar U. V. Luxburg CML 31 2 0 03 Nov 2022
Interpolating Discriminant Functions in High-Dimensional Gaussian Latent Mixtures Xin Bing M. Wegkamp 21 1 0 25 Oct 2022
Deep Linear Networks can Benignly Overfit when Shallow Ones Do Niladri S. Chatterji Philip M. Long 20 8 0 19 Sep 2022
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty Thomas George Guillaume Lajoie A. Baratin 28 5 0 19 Sep 2022
Generalization Properties of NAS under Activation and Skip Connection Search Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher AI4CE 28 15 0 15 Sep 2022
Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models Ethan Pickering T. Sapsis 24 6 0 27 Aug 2022
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition Michal Derezinski E. Rebrova 27 16 0 20 Aug 2022
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting Neil Rohit Mallinar James B. Simon Amirhesam Abedsoltan Parthe Pandit M. Belkin Preetum Nakkiran 24 37 0 14 Jul 2022
Target alignment in truncated kernel ridge regression Arash A. Amini R. Baumgartner Dai Feng 14 3 0 28 Jun 2022
Provable Generalization of Overparameterized Meta-learning Trained with SGD Yu Huang Yingbin Liang Longbo Huang MLT 26 8 0 18 Jun 2022
Beyond Ridge Regression for Distribution-Free Data Koby Bibas M. Feder 17 0 0 17 Jun 2022
Regularization-wise double descent: Why it occurs and how to eliminate it Fatih Yilmaz Reinhard Heckel 25 11 0 03 Jun 2022
A Blessing of Dimensionality in Membership Inference through Regularization Jasper Tan Daniel LeJeune Blake Mason Hamid Javadi Richard G. Baraniuk 32 18 0 27 May 2022
Proximal Estimation and Inference Alberto Quaini F. Trojani 21 1 0 26 May 2022
Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime Hong Hu Yue M. Lu 51 15 0 13 May 2022
An Equivalence Principle for the Spectrum of Random Inner-Product Kernel Matrices with Polynomial Scalings Yue M. Lu H. Yau 24 24 0 12 May 2022
Training-conditional coverage for distribution-free predictive inference Michael Bian Rina Foygel Barber 34 25 0 07 May 2022
Benign Overfitting in Time Series Linear Models with Over-Parameterization Shogo H. Nakakita Masaaki Imaizumi AI4TS 27 5 0 18 Apr 2022
Concentration of Random Feature Matrices in High-Dimensions Zhijun Chen Hayden Schaeffer Rachel A. Ward 22 6 0 14 Apr 2022
Convergence of gradient descent for deep neural networks S. Chatterjee ODL 21 20 0 30 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 49 7 0 07 Mar 2022
Estimation under Model Misspecification with Fake Features Martin Hellkvist Ayça Özçelikkale Anders Ahlén 19 11 0 07 Mar 2022
Contrasting random and learned features in deep Bayesian linear regression Jacob A. Zavatone-Veth William L. Tong C. Pehlevan BDL MLT 28 26 0 01 Mar 2022
Deep Ensembles Work, But Are They Necessary? Taiga Abe E. Kelly Buchanan Geoff Pleiss R. Zemel John P. Cunningham OOD UQCV 41 59 0 14 Feb 2022
Exact Solutions of a Deep Linear Network Liu Ziyin Botao Li Xiangmin Meng ODL 19 21 0 10 Feb 2022
HARFE: Hard-Ridge Random Feature Expansion Esha Saha Hayden Schaeffer Giang Tran 38 14 0 06 Feb 2022
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 31 10 0 31 Dec 2021
Over-Parametrized Matrix Factorization in the Presence of Spurious Stationary Points Armin Eftekhari 24 1 0 25 Dec 2021
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning Yuege Xie Bobby Shi Hayden Schaeffer Rachel A. Ward 78 9 0 07 Dec 2021
A generalization gap estimation for overparameterized models via the Langevin functional variance Akifumi Okuno Keisuke Yano 38 1 0 07 Dec 2021
Multi-scale Feature Learning Dynamics: Insights for Double Descent Mohammad Pezeshki Amartya Mitra Yoshua Bengio Guillaume Lajoie 61 25 0 06 Dec 2021
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model A. Bodin N. Macris 37 13 0 22 Oct 2021
Conditioning of Random Feature Matrices: Double Descent and Generalization Error Zhijun Chen Hayden Schaeffer 35 12 0 21 Oct 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 36 1 0 27 Sep 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 29 71 0 06 Sep 2021
Interpolation can hurt robust generalization even when there is no noise Konstantin Donhauser Alexandru cTifrea Michael Aerni Reinhard Heckel Fanny Yang 31 14 0 05 Aug 2021
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks Adityanarayanan Radhakrishnan George Stefanakis M. Belkin Caroline Uhler 30 25 0 31 Jul 2021
The loss landscape of deep linear neural networks: a second-order analysis E. M. Achour Franccois Malgouyres Sébastien Gerchinovitz ODL 24 9 0 28 Jul 2021
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression William T. Stephenson Zachary Frangella Madeleine Udell Tamara Broderick 14 12 0 19 Jul 2021
A Theoretical Analysis of Fine-tuning with Linear Teachers Gal Shachaf Alon Brutzkus Amir Globerson 31 17 0 04 Jul 2021
Random Neural Networks in the Infinite Width Limit as Gaussian Processes Boris Hanin BDL 24 43 0 04 Jul 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting Frederic Koehler Lijia Zhou Danica J. Sutherland Nathan Srebro 29 55 0 17 Jun 2021
Double Descent and Other Interpolation Phenomena in GANs Lorenzo Luzi Yehuda Dar Richard Baraniuk 23 5 0 07 Jun 2021
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