Deep Equals Shallow for ReLU Networks in Kernel Regimes

30 September 2020

Papers citing "Deep Equals Shallow for ReLU Networks in Kernel Regimes"

50 / 69 papers shown

Title
Super-fast rates of convergence for Neural Networks Classifiers under the Hard Margin Condition Nathanael Tepakbong Ding-Xuan Zhou Xiang Zhou 33 0 0 13 May 2025
Fractal and Regular Geometry of Deep Neural Networks Simmaco Di Lillo Domenico Marinucci Michele Salvi S. Vigogna MDE AI4CE 31 0 0 08 Apr 2025
Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators Weiye Gan Yicheng Li Q. Lin Zuoqiang Shi 39 0 0 14 Mar 2025
A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis Akash Kumar Rahul Parhi Mikhail Belkin 41 0 0 22 Feb 2025
Gradient Descent Finds Over-Parameterized Neural Networks with Sharp Generalization for Nonparametric Regression Yingzhen Yang Ping Li MLT 32 0 0 05 Nov 2024
Sample-efficient Bayesian Optimisation Using Known Invariances Theodore Brown Alexandru Cioba Ilija Bogunovic 28 2 0 22 Oct 2024
A Lipschitz spaces view of infinitely wide shallow neural networks Francesca Bartolucci Marcello Carioni José A. Iglesias Yury Korolev Emanuele Naldi S. Vigogna 16 0 0 18 Oct 2024
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory Guhan Chen Yicheng Li Qian Lin AAML 38 1 0 08 Oct 2024
Improving Adaptivity via Over-Parameterization in Sequence Models Yicheng Li Qian Lin 27 1 0 02 Sep 2024
Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension Kedar Karhadkar Michael Murray Guido Montúfar 32 2 0 23 May 2024
Spectral complexity of deep neural networks Simmaco Di Lillo Domenico Marinucci Michele Salvi S. Vigogna BDL 74 1 0 15 May 2024
Sliding down the stairs: how correlated latent variables accelerate learning with neural networks Lorenzo Bardone Sebastian Goldt 30 7 0 12 Apr 2024
Neural reproducing kernel Banach spaces and representer theorems for deep networks Francesca Bartolucci E. De Vito Lorenzo Rosasco S. Vigogna 44 4 0 13 Mar 2024
Towards Understanding Inductive Bias in Transformers: A View From Infinity Itay Lavie Guy Gur-Ari Z. Ringel 32 1 0 07 Feb 2024
Generalization in Kernel Regression Under Realistic Assumptions Daniel Barzilai Ohad Shamir 29 14 0 26 Dec 2023
On the Nystrom Approximation for Preconditioning in Kernel Machines Amirhesam Abedsoltan Parthe Pandit Luis Rademacher Misha Belkin 14 3 0 06 Dec 2023
The Expressive Power of Low-Rank Adaptation Yuchen Zeng Kangwook Lee 28 49 0 26 Oct 2023
On the Foundations of Shortcut Learning Katherine Hermann Hossein Mobahi Thomas Fel M. C. Mozer VLM 30 25 0 24 Oct 2023
On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay Yicheng Li Hao Zhang Qian Lin 27 12 0 23 Sep 2023
How many Neurons do we need? A refined Analysis for Shallow Networks trained with Gradient Descent Mike Nguyen Nicole Mücke MLT 14 5 0 14 Sep 2023
Optimal Rate of Kernel Regression in Large Dimensions Weihao Lu Hao Zhang Yicheng Li Manyun Xu Qian Lin 34 5 0 08 Sep 2023
Non-Parametric Representation Learning with Kernels P. Esser Maximilian Fleissner D. Ghoshdastidar SSL 21 4 0 05 Sep 2023
Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum Amnon Geifman Daniel Barzilai Ronen Basri Meirav Galun 24 4 0 26 Jul 2023
Quantitative CLTs in Deep Neural Networks Stefano Favaro Boris Hanin Domenico Marinucci I. Nourdin G. Peccati BDL 23 11 0 12 Jul 2023
Kernels, Data & Physics Francesco Cagnetta Deborah Oliveira Mahalakshmi Sabanayagam Nikolaos Tsilivis Julia Kempe 25 0 0 05 Jul 2023
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space Zhengdao Chen 28 1 0 03 Jul 2023
A Quantitative Functional Central Limit Theorem for Shallow Neural Networks Valentina Cammarota Domenico Marinucci M. Salvi S. Vigogna 34 7 0 29 Jun 2023
$The $L^\infty$ Learnability of Reproducing Kernel Hilbert Spaces$ The $L^\infty$ Learnability of Reproducing Kernel Hilbert Spaces Hongrui Chen Jihao Long Lei Wu 8 0 0 05 Jun 2023
A Rainbow in Deep Network Black Boxes Florentin Guth Brice Ménard G. Rochette S. Mallat 17 10 0 29 May 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension Moritz Haas David Holzmüller U. V. Luxburg Ingo Steinwart MLT 35 13 0 23 May 2023
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks Chanwoo Chun Daniel D. Lee BDL 33 2 0 17 May 2023
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains Yicheng Li Zixiong Yu Y. Cotronis Qian Lin 55 13 0 04 May 2023
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits Yusha Liu Aarti Singh 11 1 0 26 Apr 2023
Sparse Gaussian Processes with Spherical Harmonic Features Revisited Stefanos Eleftheriadis Dominic Richards J. Hensman 14 1 0 28 Mar 2023
Kernel interpolation generalizes poorly Yicheng Li Haobo Zhang Qian Lin 29 10 0 28 Mar 2023
$Generalization Ability of Wide Neural Networks on $\mathbb{R}$$ Generalization Ability of Wide Neural Networks on $\mathbb{R}$ Jianfa Lai Manyun Xu Rui Chen Qi-Rong Lin 13 21 0 12 Feb 2023
A Kernel Perspective of Skip Connections in Convolutional Networks Daniel Barzilai Amnon Geifman Meirav Galun Ronen Basri 15 11 0 27 Nov 2022
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks Jiayu Yao Yaniv Yacoby Beau Coker Weiwei Pan Finale Doshi-Velez 19 1 0 16 Nov 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 30 11 0 15 Nov 2022
Generalization Properties of NAS under Activation and Skip Connection Search Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher AI4CE 15 14 0 15 Sep 2022
What Can Be Learnt With Wide Convolutional Neural Networks? Francesco Cagnetta Alessandro Favero M. Wyart MLT 35 11 0 01 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
Graph Neural Network Bandits Parnian Kassraie Andreas Krause Ilija Bogunovic 26 11 0 13 Jul 2022
Learning sparse features can lead to overfitting in neural networks Leonardo Petrini Francesco Cagnetta Eric Vanden-Eijnden M. Wyart MLT 29 23 0 24 Jun 2022
VC Theoretical Explanation of Double Descent Eng Hock Lee V. Cherkassky 17 3 0 31 May 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu Jose H. Blanchet Lexing Ying 30 7 0 15 May 2022
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels Amnon Geifman Meirav Galun David Jacobs Ronen Basri 19 13 0 17 Mar 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks Shaun Li AI4CE 30 0 0 03 Jan 2022
Eigenspace Restructuring: a Principle of Space and Frequency in Neural Networks Lechao Xiao 26 21 0 10 Dec 2021
Understanding Layer-wise Contributions in Deep Neural Networks through Spectral Analysis Yatin Dandi Arthur Jacot FAtt 16 4 0 06 Nov 2021