Neural Tangent Kernel: Convergence and Generalization in Neural Networks

20 June 2018

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

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Title
On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective Lili Su Pengkun Yang MLT 27 53 0 26 May 2019
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 24 183 0 24 May 2019
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks Yaoyu Zhang Zhi-Qin John Xu Tao Luo Zheng Ma MLT AI4CE 36 38 0 24 May 2019
Neural Temporal-Difference and Q-Learning Provably Converge to Global Optima Qi Cai Zhuoran Yang Jason D. Lee Zhaoran Wang 36 29 0 24 May 2019
Gradient Descent can Learn Less Over-parameterized Two-layer Neural Networks on Classification Problems Atsushi Nitanda Geoffrey Chinot Taiji Suzuki MLT 16 33 0 23 May 2019
A type of generalization error induced by initialization in deep neural networks Yaoyu Zhang Zhi-Qin John Xu Tao Luo Zheng Ma 9 50 0 19 May 2019
An Information Theoretic Interpretation to Deep Neural Networks Shao-Lun Huang Xiangxiang Xu Lizhong Zheng G. Wornell FAtt 22 41 0 16 May 2019
Do Kernel and Neural Embeddings Help in Training and Generalization? Arman Rahbar Emilio Jorge Devdatt Dubhashi Morteza Haghir Chehreghani MLT 25 0 0 13 May 2019
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study Daniel S. Park Jascha Narain Sohl-Dickstein Quoc V. Le Samuel L. Smith 27 57 0 09 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 25 109 0 09 May 2019
Similarity of Neural Network Representations Revisited Simon Kornblith Mohammad Norouzi Honglak Lee Geoffrey E. Hinton 70 1,361 0 01 May 2019
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 18 241 0 27 Apr 2019
On Exact Computation with an Infinitely Wide Neural Net Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang 44 905 0 26 Apr 2019
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process Guy Blanc Neha Gupta Gregory Valiant Paul Valiant 24 144 0 19 Apr 2019
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent Karthik A. Sankararaman Soham De Zheng Xu Yifan Jiang Tom Goldstein ODL 27 103 0 15 Apr 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 38 136 0 10 Apr 2019
Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections E. Weinan Chao Ma Qingcan Wang Lei Wu MLT 37 22 0 10 Apr 2019
A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics E. Weinan Chao Ma Lei Wu MLT 19 121 0 08 Apr 2019
Convergence rates for the stochastic gradient descent method for non-convex objective functions Benjamin J. Fehrman Benjamin Gess Arnulf Jentzen 19 101 0 02 Apr 2019
On the Power and Limitations of Random Features for Understanding Neural Networks Gilad Yehudai Ohad Shamir MLT 28 181 0 01 Apr 2019
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks Mingchen Li Mahdi Soltanolkotabi Samet Oymak NoLa 47 351 0 27 Mar 2019
General Probabilistic Surface Optimization and Log Density Estimation Dmitry Kopitkov Vadim Indelman 8 1 0 25 Mar 2019
Towards Characterizing Divergence in Deep Q-Learning Joshua Achiam Ethan Knight Pieter Abbeel 27 96 0 21 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset R. Tibshirani 31 728 0 19 Mar 2019
Stabilize Deep ResNet with A Sharp Scaling Factor $τ$ Huishuai Zhang Da Yu Mingyang Yi Wei Chen Tie-Yan Liu 32 8 0 17 Mar 2019
Mean Field Analysis of Deep Neural Networks Justin A. Sirignano K. Spiliopoulos 22 82 0 11 Mar 2019
Function Space Particle Optimization for Bayesian Neural Networks Ziyu Wang Tongzheng Ren Jun Zhu Bo Zhang BDL 28 63 0 26 Feb 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 52 1,077 0 18 Feb 2019
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit Song Mei Theodor Misiakiewicz Andrea Montanari MLT 33 276 0 16 Feb 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation Greg Yang 11 284 0 13 Feb 2019
Uniform convergence may be unable to explain generalization in deep learning Vaishnavh Nagarajan J. Zico Kolter MoMe AI4CE 17 309 0 13 Feb 2019
Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks Phan-Minh Nguyen AI4CE 24 72 0 07 Feb 2019
Are All Layers Created Equal? Chiyuan Zhang Samy Bengio Y. Singer 20 140 0 06 Feb 2019
Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks Yuan Cao Quanquan Gu ODL MLT AI4CE 25 155 0 04 Feb 2019
Stiffness: A New Perspective on Generalization in Neural Networks Stanislav Fort Pawel Krzysztof Nowak Stanislaw Jastrzebski S. Narayanan 21 94 0 28 Jan 2019
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs D. Gilboa B. Chang Minmin Chen Greg Yang S. Schoenholz Ed H. Chi Jeffrey Pennington 34 40 0 25 Jan 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 55 961 0 24 Jan 2019
Training Neural Networks as Learning Data-adaptive Kernels: Provable Representation and Approximation Benefits Xialiang Dou Tengyuan Liang MLT 29 43 0 21 Jan 2019
A Theoretical Analysis of Deep Q-Learning Jianqing Fan Zhuoran Yang Yuchen Xie Zhaoran Wang 23 595 0 01 Jan 2019
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins Dawei Li Tian Ding Ruoyu Sun 29 38 0 28 Dec 2018
On Lazy Training in Differentiable Programming Lénaïc Chizat Edouard Oyallon Francis R. Bach 46 807 0 19 Dec 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 32 765 0 12 Nov 2018
A Convergence Theory for Deep Learning via Over-Parameterization Zeyuan Allen-Zhu Yuanzhi Li Zhao Song AI4CE ODL 51 1,448 0 09 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du J. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 44 1,125 0 09 Nov 2018
On the Convergence Rate of Training Recurrent Neural Networks Zeyuan Allen-Zhu Yuanzhi Li Zhao Song 29 191 0 29 Oct 2018
A jamming transition from under- to over-parametrization affects loss landscape and generalization S. Spigler Mario Geiger Stéphane dÁscoli Levent Sagun Giulio Biroli M. Wyart 27 151 0 22 Oct 2018
Exchangeability and Kernel Invariance in Trained MLPs Russell Tsuchida Fred Roosta M. Gallagher 14 3 0 19 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei J. Lee Qiang Liu Tengyu Ma 26 245 0 12 Oct 2018
Information Geometry of Orthogonal Initializations and Training Piotr A. Sokól Il-Su Park AI4CE 80 16 0 09 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 56 1,252 0 04 Oct 2018