The generalization error of random features regression: Precise asymptotics and double descent curve

14 August 2019

Papers citing "The generalization error of random features regression: Precise asymptotics and double descent curve"

50 / 240 papers shown

Title
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Yuanzhe Hu Kinshuk Goel Vlad Killiakov Yaoqing Yang 70 2 0 06 Jun 2025
Models of Heavy-Tailed Mechanistic Universality Liam Hodgkinson Zhichao Wang Michael W. Mahoney 84 1 0 04 Jun 2025
Statistical mechanics of extensive-width Bayesian neural networks near interpolation Jean Barbier Francesco Camilli Minh-Toan Nguyen Mauro Pastore Rudy Skerk 49 0 0 30 May 2025
On the Emergence of Weak-to-Strong Generalization: A Bias-Variance Perspective Gengze Xu Wei Yao Ziqiao Wang Yong Liu 54 0 0 30 May 2025
Directional Convergence, Benign Overfitting of Gradient Descent in leaky ReLU two-layer Neural Networks Ichiro Hashimoto MLT 81 0 0 22 May 2025
A dynamic view of the double descent Vivek Shripad Borkar 160 0 0 03 May 2025
Deep learning with missing data Tianyi Ma Tengyao Wang R. Samworth 279 1 0 21 Apr 2025
Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational Geometry Chi-Ning Chou Hang Le Yichen Wang SueYeon Chung 95 0 0 23 Mar 2025
Quantifying Overfitting along the Regularization Path for Two-Part-Code MDL in Supervised Classification Xiaohan Zhu Nathan Srebro 127 0 0 03 Mar 2025
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model O. Duranthon L. Zdeborová 116 0 0 03 Mar 2025
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure Samet Demir Zafer Dogan MLT 94 0 0 02 Mar 2025
Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks Rylan Schaeffer Punit Singh Koura Binh Tang R. Subramanian Aaditya K. Singh ... Vedanuj Goswami Sergey Edunov Dieuwke Hupkes Sanmi Koyejo Sharan Narang ALM 158 1 0 24 Feb 2025
Feature maps for the Laplacian kernel and its generalizations Sudhendu Ahir Parthe Pandit 103 0 0 24 Feb 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer Blake Bordelon Cengiz Pehlevan AI4CE 274 1 0 04 Feb 2025
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Simone Bombari Marco Mondelli 325 0 0 03 Feb 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs Kasimir Tanner Matteo Vilucchio Bruno Loureiro Florent Krzakala AAML 107 1 0 31 Dec 2024
Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm Xiaosi Gu Tomoyuki Obuchi 149 0 0 29 Nov 2024
Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity Mouin Ben Ammar David Brellmann Arturo Mendoza Antoine Manzanera Gianni Franchi OODD 120 0 0 04 Nov 2024
High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws M. E. Ildiz Halil Alperen Gozeten Ege Onur Taga Marco Mondelli Samet Oymak 137 5 0 24 Oct 2024
Theoretical Limitations of Ensembles in the Age of Overparameterization Niclas Dern John P. Cunningham Geoff Pleiss BDL UQCV 98 1 0 21 Oct 2024
Provable Weak-to-Strong Generalization via Benign Overfitting David X. Wu A. Sahai 165 11 0 06 Oct 2024
On the Pinsker bound of inner product kernel regression in large dimensions Weihao Lu Jialin Ding Haobo Zhang Qian Lin 95 1 0 02 Sep 2024
How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang Edmilson Roque dos Santos Huixin Zhang Sean P. Cornelius 156 2 0 11 Jul 2024
Precise analysis of ridge interpolators under heavy correlations -- a Random Duality Theory view Mihailo Stojnic 62 1 0 13 Jun 2024
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning Fan He Mingzhe He Lei Shi Xiaolin Huang Johan A. K. Suykens 83 1 0 03 Jun 2024
High-dimensional Learning with Noisy Labels Aymane El Firdoussi M. Seddik NoLa 33 0 0 23 May 2024
Asymptotic theory of in-context learning by linear attention Yue M. Lu Mary I. Letey Jacob A. Zavatone-Veth Anindita Maiti Cengiz Pehlevan 118 16 0 20 May 2024
Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis Yufan Li Subhabrata Sen Ben Adlam MLT 179 1 0 18 Apr 2024
Predictive Churn with the Set of Good Models J. Watson-Daniels Flavio du Pin Calmon Alexander DÁmour Carol Xuan Long David C. Parkes Berk Ustun 147 8 0 12 Feb 2024
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions Adel Javanmard Lin Chen Vahab Mirrokni Ashwinkumar Badanidiyuru Gang Fu 73 2 0 20 Jan 2024
Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem Simon Segert 99 0 0 18 Nov 2023
Orthogonal Random Features: Explicit Forms and Sharp Inequalities N. Demni Hachem Kadri 74 1 0 11 Oct 2023
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks Behrad Moniri Donghwan Lee Hamed Hassani Yan Sun MLT 104 23 0 11 Oct 2023
Six Lectures on Linearized Neural Networks Theodor Misiakiewicz Andrea Montanari 148 13 0 25 Aug 2023
Quantitative CLTs in Deep Neural Networks Stefano Favaro Boris Hanin Domenico Marinucci I. Nourdin G. Peccati BDL 138 16 0 12 Jul 2023
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models David X. Wu A. Sahai 105 3 0 23 Jun 2023
Benign Overfitting in Deep Neural Networks under Lazy Training Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos Francesco Locatello Volkan Cevher AI4CE 71 10 0 30 May 2023
Generalized equivalences between subsampling and ridge regularization Pratik V. Patil Jin-Hong Du 100 5 0 29 May 2023
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time Yatin Dandi Florent Krzakala Bruno Loureiro Luca Pesce Ludovic Stephan MLT 136 29 0 29 May 2023
How many samples are needed to leverage smoothness? Vivien A. Cabannes Stefano Vigogna 72 2 0 25 May 2023
From Tempered to Benign Overfitting in ReLU Neural Networks Guy Kornowski Gilad Yehudai Ohad Shamir 91 13 0 24 May 2023
Deep neural networks have an inbuilt Occam's razor Chris Mingard Henry Rees Guillermo Valle Pérez A. Louis UQCV BDL 89 16 0 13 Apr 2023
Per-Example Gradient Regularization Improves Learning Signals from Noisy Data Xuran Meng Yuan Cao Difan Zou 80 5 0 31 Mar 2023
Kernel interpolation generalizes poorly Yicheng Li Haobo Zhang Qian Lin 83 11 0 28 Mar 2023
Online Learning for the Random Feature Model in the Student-Teacher Framework Roman Worschech B. Rosenow 93 0 0 24 Mar 2023
Learning curves for deep structured Gaussian feature models Jacob A. Zavatone-Veth Cengiz Pehlevan MLT 95 11 0 01 Mar 2023
Some Fundamental Aspects about Lipschitz Continuity of Neural Networks Grigory Khromov Sidak Pal Singh 168 8 0 21 Feb 2023
Precise Asymptotic Analysis of Deep Random Feature Models David Bosch Ashkan Panahi B. Hassibi 100 19 0 13 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width Hugo Cui Florent Krzakala Lenka Zdeborová BDL 109 39 0 01 Feb 2023
Bayesian Interpolation with Deep Linear Networks Boris Hanin Alexander Zlokapa 153 26 0 29 Dec 2022