A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent

9 June 2020

Papers citing "A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent"

16 / 16 papers shown

Title
A Model Zoo on Phase Transitions in Neural Networks Konstantin Schurholt Léo Meynent Yefan Zhou Haiquan Lu Yaoqing Yang Damian Borth 68 0 0 25 Apr 2025
KITE: A Kernel-based Improved Transferability Estimation Method Yunhui Guo 45 0 0 01 May 2024
The Universal Statistical Structure and Scaling Laws of Chaos and Turbulence Noam Levi Yaron Oz AI4CE 26 1 0 02 Nov 2023
The Interpolating Information Criterion for Overparameterized Models Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 20 7 0 15 Jul 2023
On The Relative Error of Random Fourier Features for Preserving Kernel Distance Kuan Cheng S. Jiang Luojian Wei Zhide Wei 36 1 0 01 Oct 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba Murat A. Erdogdu Taiji Suzuki Zhichao Wang Denny Wu Greg Yang MLT 34 121 0 03 May 2022
Generalized Reference Kernel for One-class Classification Jenni Raitoharju Alexandros Iosifidis 15 2 0 01 May 2022
Concentration of Random Feature Matrices in High-Dimensions Zhijun Chen Hayden Schaeffer Rachel A. Ward 22 6 0 14 Apr 2022
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning Yuege Xie Bobby Shi Hayden Schaeffer Rachel A. Ward 78 9 0 07 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
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
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi-Hua Zhou A. Gretton MLT 33 35 0 06 Jun 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
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 36 172 0 23 Apr 2020
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 30 190 0 02 Oct 2018