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Spectrally-normalized margin bounds for neural networks

26 June 2017

Papers citing "Spectrally-normalized margin bounds for neural networks"

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Title
Orthogonal Statistical Learning Dylan J. Foster Vasilis Syrgkanis 154 174 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 234 974 0 24 Jan 2019
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples Kamil Nar Orhan Ocal S. Shankar Sastry Kannan Ramchandran AAML 90 54 0 24 Jan 2019
Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks Charles H. Martin Michael W. Mahoney 83 56 0 24 Jan 2019
Understanding Geometry of Encoder-Decoder CNNs J. C. Ye Woon Kyoung Sung 3DV AI4CE 88 74 0 22 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Yaoyu Zhang Yan Xiao Zheng Ma 137 521 0 19 Jan 2019
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis Yusuke Tsuzuku Issei Sato Masashi Sugiyama 84 77 0 15 Jan 2019
Tightening Mutual Information Based Bounds on Generalization Error Yuheng Bu Shaofeng Zou Venugopal V. Veeravalli 66 177 0 15 Jan 2019
A Theoretical Analysis of Deep Q-Learning Jianqing Fan Zhuoran Yang Yuchen Xie Zhaoran Wang 193 611 0 01 Jan 2019
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins Dawei Li Tian Ding Ruoyu Sun 120 38 0 28 Dec 2018
On Computation and Generalization of GANs with Spectrum Control Haoming Jiang Zhehui Chen Minshuo Chen Feng Liu Dingding Wang T. Zhao 69 6 0 28 Dec 2018
Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution Shen-Huan Lyu Lu Wang Zhi Zhou 41 11 0 27 Dec 2018
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? Samet Oymak Mahdi Soltanolkotabi ODL 73 177 0 25 Dec 2018
Learning finite-dimensional coding schemes with nonlinear reconstruction maps Jaeho Lee Maxim Raginsky 56 9 0 23 Dec 2018
On a Sparse Shortcut Topology of Artificial Neural Networks Fenglei Fan Dayang Wang Hengtao Guo Qikui Zhu Pingkun Yan Ge Wang Hengyong Yu 135 22 0 22 Nov 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 254 448 0 21 Nov 2018
Analytic Network Learning Kar-Ann Toh 44 9 0 20 Nov 2018
Neural Lander: Stable Drone Landing Control using Learned Dynamics Guanya Shi Xichen Shi Michael O'Connell Rose Yu Kamyar Azizzadenesheli Anima Anandkumar Yisong Yue Soon-Jo Chung 115 276 0 19 Nov 2018
Generalizable Adversarial Training via Spectral Normalization Farzan Farnia Jesse M. Zhang David Tse OOD AAML 83 140 0 19 Nov 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 96 325 0 13 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 72 68 0 13 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 223 775 0 12 Nov 2018
Sample Compression, Support Vectors, and Generalization in Deep Learning Christopher Snyder S. Vishwanath MLT 75 5 0 05 Nov 2018
Minimax Estimation of Neural Net Distance Kaiyi Ji Yingbin Liang GAN 39 9 0 02 Nov 2018
A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model Yujia Wang Nhat Ho David J. Miller Anima Anandkumar Michael I. Jordan Richard G. Baraniuk BDL GAN 96 8 0 01 Nov 2018
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation Matthew O'Kelly Aman Sinha Hongseok Namkoong John C. Duchi Russ Tedrake 121 217 0 31 Oct 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin Kannan Ramchandran Peter L. Bartlett AAML 105 261 0 29 Oct 2018
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications Huan Zhang Pengchuan Zhang Cho-Jui Hsieh AAML 68 63 0 28 Oct 2018
Uniform Convergence of Gradients for Non-Convex Learning and Optimization Dylan J. Foster Ayush Sekhari Karthik Sridharan 82 68 0 25 Oct 2018
Sparse DNNs with Improved Adversarial Robustness Yiwen Guo Chao Zhang Changshui Zhang Yurong Chen AAML 98 154 0 23 Oct 2018
Adversarial Risk Bounds via Function Transformation Justin Khim Po-Ling Loh AAML 90 50 0 22 Oct 2018
A Priori Estimates of the Population Risk for Two-layer Neural Networks Weinan E Chao Ma Lei Wu 92 132 0 15 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei Jason D. Lee Qiang Liu Tengyu Ma 268 245 0 12 Oct 2018
Rethinking Breiman's Dilemma in Neural Networks: Phase Transitions of Margin Dynamics Weizhi Zhu Yifei Huang Yuan Yao AI4CE OOD 20 1 0 08 Oct 2018
Detecting Memorization in ReLU Networks Edo Collins Siavash Bigdeli Sabine Süsstrunk 73 4 0 08 Oct 2018
Generalized No Free Lunch Theorem for Adversarial Robustness Elvis Dohmatob 102 28 0 08 Oct 2018
Gradient descent aligns the layers of deep linear networks Ziwei Ji Matus Telgarsky 123 257 0 04 Oct 2018
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units Yixi Xu Tianlin Li MQ 79 12 0 03 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 102 49 0 02 Oct 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 134 201 0 02 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 82 15 0 30 Sep 2018
Predicting the Generalization Gap in Deep Networks with Margin Distributions Yiding Jiang Dilip Krishnan H. Mobahi Samy Bengio UQCV 95 199 0 28 Sep 2018
An analytic theory of generalization dynamics and transfer learning in deep linear networks Andrew Kyle Lampinen Surya Ganguli OOD 92 131 0 27 Sep 2018
Capacity Control of ReLU Neural Networks by Basis-path Norm Shuxin Zheng Qi Meng Huishuai Zhang Wei-neng Chen Nenghai Yu Tie-Yan Liu 67 23 0 19 Sep 2018
Maximum-Entropy Fine-Grained Classification Abhimanyu Dubey O. Gupta Ramesh Raskar Nikhil Naik 93 157 0 16 Sep 2018
Approximation and Estimation for High-Dimensional Deep Learning Networks Andrew R. Barron Jason M. Klusowski 82 59 0 10 Sep 2018
Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations Julius Berner Philipp Grohs Arnulf Jentzen 118 183 0 09 Sep 2018
Stochastic Gradient Descent Learns State Equations with Nonlinear Activations Samet Oymak 78 43 0 09 Sep 2018
Lipschitz Networks and Distributional Robustness Zac Cranko Simon Kornblith Zhan Shi Richard Nock OOD 63 11 0 04 Sep 2018
Lipschitz regularized Deep Neural Networks generalize and are adversarially robust Chris Finlay Jeff Calder Bilal Abbasi Adam M. Oberman 95 55 0 28 Aug 2018