On the Generalization Power of Overfitted Two-Layer Neural Tangent
Kernel Models

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On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models

9 March 2021

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Papers citing "On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models"

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Title
The Dynamics of Gradient Descent for Overparametrized Neural Networks Siddhartha Satpathi R. Srikant MLT AI4CE 41 14 0 13 May 2021
A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent Zhenyu Liao Romain Couillet Michael W. Mahoney 79 93 0 09 Jun 2020
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 64 83 0 19 Feb 2020
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 69 243 0 27 Apr 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 212 746 0 19 Mar 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 201 775 0 12 Nov 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 233 1,276 0 04 Oct 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 219 653 0 03 Aug 2018
To understand deep learning we need to understand kernel learning M. Belkin Siyuan Ma Soumik Mandal 72 420 0 05 Feb 2018
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 351 4,635 0 10 Nov 2016