Neural Tangent Kernel: Convergence and Generalization in Neural Networks

20 June 2018

Papers citing "Neural Tangent Kernel: Convergence and Generalization in Neural Networks"

50 / 2,148 papers shown

Title
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks Russell Tsuchida Tim Pearce Christopher van der Heide Fred Roosta M. Gallagher 6 8 0 20 Feb 2020
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 31 82 0 19 Feb 2020
Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows G. Yoo H. Owhadi 22 21 0 19 Feb 2020
Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology Quynh N. Nguyen Marco Mondelli ODL AI4CE 21 67 0 18 Feb 2020
Learning Parities with Neural Networks Amit Daniely Eran Malach 24 76 0 18 Feb 2020
Convergence of End-to-End Training in Deep Unsupervised Contrastive Learning Zixin Wen SSL 21 2 0 17 Feb 2020
$π$ VAE: a stochastic process prior for Bayesian deep learning with MCMC Swapnil Mishra Seth Flaxman Tresnia Berah Harrison Zhu Mikko S. Pakkanen Samir Bhatt BDL 13 3 0 17 Feb 2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality Yi Zhang Orestis Plevrakis S. Du Xingguo Li Zhao-quan Song Sanjeev Arora 21 51 0 16 Feb 2020
Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? -- A Neural Tangent Kernel Perspective Kaixuan Huang Yuqing Wang Molei Tao T. Zhao MLT 14 96 0 14 Feb 2020
Self-Distillation Amplifies Regularization in Hilbert Space H. Mobahi Mehrdad Farajtabar Peter L. Bartlett 19 226 0 13 Feb 2020
Regret Bounds for Noise-Free Kernel-Based Bandits Sattar Vakili 25 3 0 12 Feb 2020
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent David Holzmüller Ingo Steinwart MLT 8 9 0 12 Feb 2020
Average-case Acceleration Through Spectral Density Estimation Fabian Pedregosa Damien Scieur 14 12 0 12 Feb 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 21 327 0 11 Feb 2020
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks Zixiang Chen Yuan Cao Quanquan Gu Tong Zhang MLT 29 10 0 10 Feb 2020
Taylorized Training: Towards Better Approximation of Neural Network Training at Finite Width Yu Bai Ben Krause Huan Wang Caiming Xiong R. Socher 8 22 0 10 Feb 2020
Distribution Approximation and Statistical Estimation Guarantees of Generative Adversarial Networks Minshuo Chen Wenjing Liao H. Zha Tuo Zhao 26 15 0 10 Feb 2020
Characterizing Structural Regularities of Labeled Data in Overparameterized Models Ziheng Jiang Chiyuan Zhang Kunal Talwar Michael C. Mozer TDI 17 97 0 08 Feb 2020
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing Elan Rosenfeld Ezra Winston Pradeep Ravikumar J. Zico Kolter OOD AAML 8 155 0 07 Feb 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 109 130 0 07 Feb 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar Cengiz Pehlevan 144 201 0 07 Feb 2020
Quasi-Equivalence of Width and Depth of Neural Networks Fenglei Fan Rongjie Lai Ge Wang 22 11 0 06 Feb 2020
Almost Sure Convergence of Dropout Algorithms for Neural Networks Albert Senen-Cerda J. Sanders 21 8 0 06 Feb 2020
Minimax Value Interval for Off-Policy Evaluation and Policy Optimization Nan Jiang Jiawei Huang OffRL 28 17 0 06 Feb 2020
A Deep Conditioning Treatment of Neural Networks Naman Agarwal Pranjal Awasthi Satyen Kale AI4CE 25 15 0 04 Feb 2020
A Corrective View of Neural Networks: Representation, Memorization and Learning Guy Bresler Dheeraj M. Nagaraj MLT 18 18 0 01 Feb 2020
Gating creates slow modes and controls phase-space complexity in GRUs and LSTMs T. Can K. Krishnamurthy D. Schwab AI4CE 6 17 0 31 Jan 2020
A Rigorous Framework for the Mean Field Limit of Multilayer Neural Networks Phan-Minh Nguyen H. Pham AI4CE 24 81 0 30 Jan 2020
On Random Kernels of Residual Architectures Etai Littwin Tomer Galanti Lior Wolf 6 4 0 28 Jan 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 261 4,489 0 23 Jan 2020
On the infinite width limit of neural networks with a standard parameterization Jascha Narain Sohl-Dickstein Roman Novak S. Schoenholz Jaehoon Lee 26 47 0 21 Jan 2020
Any Target Function Exists in a Neighborhood of Any Sufficiently Wide Random Network: A Geometrical Perspective S. Amari 27 12 0 20 Jan 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 67 247 0 09 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 38 300 0 08 Jan 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 35 19 0 31 Dec 2019
Disentangling Trainability and Generalization in Deep Neural Networks Lechao Xiao Jeffrey Pennington S. Schoenholz 6 34 0 30 Dec 2019
Deep Graph Similarity Learning: A Survey Guixiang Ma Nesreen Ahmed Theodore L. Willke Philip S. Yu GNN 21 77 0 25 Dec 2019
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks A. Shevchenko Marco Mondelli 21 37 0 20 Dec 2019
Optimization for deep learning: theory and algorithms Ruoyu Sun ODL 19 168 0 19 Dec 2019
Analytic expressions for the output evolution of a deep neural network Anastasia Borovykh 6 0 0 18 Dec 2019
Frivolous Units: Wider Networks Are Not Really That Wide Stephen Casper Xavier Boix Vanessa D’Amario Ling Guo Martin Schrimpf Kasper Vinken Gabriel Kreiman 20 19 0 10 Dec 2019
A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation Pan Xu Quanquan Gu 13 66 0 10 Dec 2019
A priori generalization error for two-layer ReLU neural network through minimum norm solution Zhi-Qin John Xu Jiwei Zhang Yaoyu Zhang Chengchao Zhao MLT 6 1 0 06 Dec 2019
Observational Overfitting in Reinforcement Learning Xingyou Song Yiding Jiang Stephen Tu Yilun Du Behnam Neyshabur OffRL 33 138 0 06 Dec 2019
Neural Tangents: Fast and Easy Infinite Neural Networks in Python Roman Novak Lechao Xiao Jiri Hron Jaehoon Lee Alexander A. Alemi Jascha Narain Sohl-Dickstein S. Schoenholz 27 224 0 05 Dec 2019
Towards Understanding the Spectral Bias of Deep Learning Yuan Cao Zhiying Fang Yue Wu Ding-Xuan Zhou Quanquan Gu 32 214 0 03 Dec 2019
Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon Jeremiah Zhe Liu BDL 15 8 0 03 Dec 2019
A Random Matrix Perspective on Mixtures of Nonlinearities for Deep Learning Ben Adlam J. Levinson Jeffrey Pennington 27 23 0 02 Dec 2019
On the optimality of kernels for high-dimensional clustering L. C. Vankadara D. Ghoshdastidar 26 11 0 01 Dec 2019
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks Umut Simsekli Mert Gurbuzbalaban T. H. Nguyen G. Richard Levent Sagun 23 55 0 29 Nov 2019