Spectrally-normalized margin bounds for neural networks

26 June 2017

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

50 / 803 papers shown

Title
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins Dawei Li Tian Ding Ruoyu Sun 18 37 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 11 6 0 28 Dec 2018
Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution Shen-Huan Lyu Lu Wang Zhi-Hua Zhou 22 11 0 27 Dec 2018
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? Samet Oymak Mahdi Soltanolkotabi ODL 6 177 0 25 Dec 2018
Learning finite-dimensional coding schemes with nonlinear reconstruction maps Jaeho Lee Maxim Raginsky 12 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 38 21 0 22 Nov 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 22 446 0 21 Nov 2018
Analytic Network Learning Kar-Ann Toh 11 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 16 270 0 19 Nov 2018
Generalizable Adversarial Training via Spectral Normalization Farzan Farnia Jesse M. Zhang David Tse OOD AAML 37 137 0 19 Nov 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 17 316 0 13 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 13 68 0 13 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 9 765 0 12 Nov 2018
Sample Compression, Support Vectors, and Generalization in Deep Learning Christopher Snyder S. Vishwanath MLT 14 5 0 05 Nov 2018
Minimax Estimation of Neural Net Distance Kaiyi Ji Yingbin Liang GAN 17 8 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 27 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 6 211 0 31 Oct 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin K. Ramchandran Peter L. Bartlett AAML 8 257 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 27 63 0 28 Oct 2018
Uniform Convergence of Gradients for Non-Convex Learning and Optimization Dylan J. Foster Ayush Sekhari Karthik Sridharan 20 68 0 25 Oct 2018
Sparse DNNs with Improved Adversarial Robustness Yiwen Guo Chao Zhang Changshui Zhang Yurong Chen AAML 17 151 0 23 Oct 2018
Adversarial Risk Bounds via Function Transformation Justin Khim Po-Ling Loh AAML 14 49 0 22 Oct 2018
A Priori Estimates of the Population Risk for Two-layer Neural Networks Weinan E Chao Ma Lei Wu 27 130 0 15 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei J. Lee Qiang Liu Tengyu Ma 18 243 0 12 Oct 2018
Rethinking Breiman's Dilemma in Neural Networks: Phase Transitions of Margin Dynamics Weizhi Zhu Yifei Huang Y. Yao AI4CE OOD 6 1 0 08 Oct 2018
Detecting Memorization in ReLU Networks Edo Collins Siavash Bigdeli Sabine Süsstrunk 34 4 0 08 Oct 2018
Generalized No Free Lunch Theorem for Adversarial Robustness Elvis Dohmatob 11 28 0 08 Oct 2018
Gradient descent aligns the layers of deep linear networks Ziwei Ji Matus Telgarsky 14 247 0 04 Oct 2018
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units Yixi Xu Xiao Wang MQ 23 12 0 03 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 23 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 30 190 0 02 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 11 15 0 30 Sep 2018
Predicting the Generalization Gap in Deep Networks with Margin Distributions Yiding Jiang Dilip Krishnan H. Mobahi Samy Bengio UQCV 19 198 0 28 Sep 2018
An analytic theory of generalization dynamics and transfer learning in deep linear networks Andrew Kyle Lampinen Surya Ganguli OOD 25 127 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 24 23 0 19 Sep 2018
Maximum-Entropy Fine-Grained Classification Abhimanyu Dubey O. Gupta Ramesh Raskar Nikhil Naik 11 156 0 16 Sep 2018
Approximation and Estimation for High-Dimensional Deep Learning Networks Andrew R. Barron Jason M. Klusowski 21 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 4 181 0 09 Sep 2018
Stochastic Gradient Descent Learns State Equations with Nonlinear Activations Samet Oymak 11 43 0 09 Sep 2018
Lipschitz Networks and Distributional Robustness Zac Cranko Simon Kornblith Zhan Shi Richard Nock OOD 16 11 0 04 Sep 2018
Lipschitz regularized Deep Neural Networks generalize and are adversarially robust Chris Finlay Jeff Calder Bilal Abbasi Adam M. Oberman 24 55 0 28 Aug 2018
Mean Field Analysis of Neural Networks: A Central Limit Theorem Justin A. Sirignano K. Spiliopoulos MLT 24 192 0 28 Aug 2018
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error Taiji Suzuki Hiroshi Abe Tomoya Murata Shingo Horiuchi Kotaro Ito Tokuma Wachi So Hirai Masatoshi Yukishima Tomoaki Nishimura MLT 17 10 0 26 Aug 2018
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization G. Wang G. Giannakis Jie Chen MLT 22 131 0 14 Aug 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 23 650 0 03 Aug 2018
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 21 109 0 03 Aug 2018
A Surprising Linear Relationship Predicts Test Performance in Deep Networks Q. Liao Brando Miranda Andrzej Banburski Jack Hidary T. Poggio 16 32 0 25 Jul 2018
Learning Deep Hidden Nonlinear Dynamics from Aggregate Data Yisen Wang Bo Dai Lingkai Kong S. Erfani James Bailey H. Zha DiffM 14 10 0 22 Jul 2018
Theory IIIb: Generalization in Deep Networks T. Poggio Q. Liao Brando Miranda Andrzej Banburski Xavier Boix Jack Hidary ODL AI4CE 27 26 0 29 Jun 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate M. Belkin Daniel J. Hsu P. Mitra AI4CE 26 256 0 13 Jun 2018