The Spectral Norm of Random Inner-Product Kernel Matrices

19 July 2015

Papers citing "The Spectral Norm of Random Inner-Product Kernel Matrices"

10 / 10 papers shown

Title
Demystifying Disagreement-on-the-Line in High Dimensions Dong-Hwan Lee Behrad Moniri Xinmeng Huang Edgar Dobriban Hamed Hassani 19 8 0 31 Jan 2023
An Equivalence Principle for the Spectrum of Random Inner-Product Kernel Matrices with Polynomial Scalings Yue M. Lu H. Yau 19 24 0 12 May 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 29 121 0 03 May 2022
Concentration of Random Feature Matrices in High-Dimensions Zhijun Chen Hayden Schaeffer Rachel A. Ward 20 6 0 14 Apr 2022
Learning Low-Dimensional Nonlinear Structures from High-Dimensional Noisy Data: An Integral Operator Approach Xiucai Ding Rongkai Ma 23 9 0 28 Feb 2022
Conditioning of Random Feature Matrices: Double Descent and Generalization Error Zhijun Chen Hayden Schaeffer 35 12 0 21 Oct 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 20 135 0 16 Feb 2021
The Gaussian equivalence of generative models for learning with shallow neural networks Sebastian Goldt Bruno Loureiro Galen Reeves Florent Krzakala M. Mézard Lenka Zdeborová BDL 33 100 0 25 Jun 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
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 39 624 0 14 Aug 2019