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Gradient Descent Finds Global Minima of Deep Neural Networks

9 November 2018

Papers citing "Gradient Descent Finds Global Minima of Deep Neural Networks"

50 / 466 papers shown

Title
An Improved Analysis of Training Over-parameterized Deep Neural Networks Difan Zou Quanquan Gu 77 235 0 11 Jun 2019
Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound Zhao Song Xin Yang 75 91 0 09 Jun 2019
A mean-field limit for certain deep neural networks Dyego Araújo R. Oliveira Daniel Yukimura AI4CE 82 70 0 01 Jun 2019
What Can Neural Networks Reason About? Keyulu Xu Jingling Li Mozhi Zhang S. Du Ken-ichi Kawarabayashi Stefanie Jegelka NAI AI4CE 106 248 0 30 May 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks Yuan Cao Quanquan Gu MLT AI4CE 125 392 0 30 May 2019
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels S. Du Kangcheng Hou Barnabás Póczós Ruslan Salakhutdinov Ruosong Wang Keyulu Xu 142 276 0 30 May 2019
Generalization bounds for deep convolutional neural networks Philip M. Long Hanie Sedghi MLT 136 90 0 29 May 2019
On the Inductive Bias of Neural Tangent Kernels A. Bietti Julien Mairal 122 260 0 29 May 2019
Gram-Gauss-Newton Method: Learning Overparameterized Neural Networks for Regression Problems Tianle Cai Ruiqi Gao Jikai Hou Siyu Chen Dong Wang Di He Zhihua Zhang Liwei Wang ODL 71 57 0 28 May 2019
Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks Guodong Zhang James Martens Roger C. Grosse ODL 113 126 0 27 May 2019
Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes Andrea Agazzi Jianfeng Lu 93 8 0 27 May 2019
On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective Lili Su Pengkun Yang MLT 78 54 0 26 May 2019
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 416 183 0 24 May 2019
On the Learning Dynamics of Two-layer Nonlinear Convolutional Neural Networks Ting Yu Junzhao Zhang Zhanxing Zhu MLT 44 5 0 24 May 2019
How degenerate is the parametrization of neural networks with the ReLU activation function? Julius Berner Dennis Elbrächter Philipp Grohs ODL 96 28 0 23 May 2019
Exploring Structural Sparsity of Deep Networks via Inverse Scale Spaces Yanwei Fu Chen Liu Donghao Li Zuyuan Zhong Xinwei Sun Jinshan Zeng Yuan Yao 46 10 0 23 May 2019
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints Mengtian Li Ersin Yumer Deva Ramanan 72 49 0 12 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 85 110 0 09 May 2019
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 97 243 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 283 928 0 26 Apr 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 206 135 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 108 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 80 124 0 08 Apr 2019
Stokes Inversion based on Convolutional Neural Networks A. Ramos Institute for Solar Physics 40 45 0 07 Apr 2019
Every Local Minimum Value is the Global Minimum Value of Induced Model in Non-convex Machine Learning Kenji Kawaguchi Jiaoyang Huang L. Kaelbling AAML 96 18 0 07 Apr 2019
Convergence rates for the stochastic gradient descent method for non-convex objective functions Benjamin J. Fehrman Benjamin Gess Arnulf Jentzen 98 101 0 02 Apr 2019
On the Power and Limitations of Random Features for Understanding Neural Networks Gilad Yehudai Ohad Shamir MLT 125 182 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 140 355 0 27 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 291 747 0 19 Mar 2019
Stabilize Deep ResNet with A Sharp Scaling Factor $τ$ Huishuai Zhang Da Yu Mingyang Yi Wei Chen Tie-Yan Liu 57 9 0 17 Mar 2019
Mean Field Analysis of Deep Neural Networks Justin A. Sirignano K. Spiliopoulos 105 82 0 11 Mar 2019
A Priori Estimates of the Population Risk for Residual Networks E. Weinan Chao Ma Qingcan Wang UQCV 103 61 0 06 Mar 2019
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods Maher Nouiehed Maziar Sanjabi Tianjian Huang Jason D. Lee Meisam Razaviyayn 113 344 0 21 Feb 2019
Global Convergence of Adaptive Gradient Methods for An Over-parameterized Neural Network Xiaoxia Wu S. Du Rachel A. Ward 103 66 0 19 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 224 1,112 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 90 280 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 202 289 0 13 Feb 2019
Identity Crisis: Memorization and Generalization under Extreme Overparameterization Chiyuan Zhang Samy Bengio Moritz Hardt Michael C. Mozer Y. Singer 60 90 0 13 Feb 2019
Towards moderate overparameterization: global convergence guarantees for training shallow neural networks Samet Oymak Mahdi Soltanolkotabi 75 323 0 12 Feb 2019
Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks Phan-Minh Nguyen AI4CE 79 72 0 07 Feb 2019
Are All Layers Created Equal? Chiyuan Zhang Samy Bengio Y. Singer 111 140 0 06 Feb 2019
Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks Yuan Cao Quanquan Gu ODL MLT AI4CE 151 158 0 04 Feb 2019
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning Jian Li Xuanyuan Luo Mingda Qiao 73 89 0 02 Feb 2019
Depth creates no more spurious local minima Li Zhang 65 19 0 28 Jan 2019
Stiffness: A New Perspective on Generalization in Neural Networks Stanislav Fort Pawel Krzysztof Nowak Stanislaw Jastrzebski S. Narayanan 138 94 0 28 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 234 974 0 24 Jan 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks S. Du Wei Hu 115 95 0 24 Jan 2019
On Connected Sublevel Sets in Deep Learning Quynh N. Nguyen 134 102 0 22 Jan 2019
Elimination of All Bad Local Minima in Deep Learning Kenji Kawaguchi L. Kaelbling 102 45 0 02 Jan 2019
A Theoretical Analysis of Deep Q-Learning Jianqing Fan Zhuoran Yang Yuchen Xie Zhaoran Wang 203 611 0 01 Jan 2019