Exploring Generalization in Deep Learning

27 June 2017

Srinadh Bhojanapalli

Papers citing "Exploring Generalization in Deep Learning"

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Title
Sample Compression, Support Vectors, and Generalization in Deep Learning Christopher Snyder S. Vishwanath MLT 16 5 0 05 Nov 2018
Nonlinear Collaborative Scheme for Deep Neural Networks Hui-Ling Zhen Xi Lin Alan Tang Zhenhua Li Qingfu Zhang Sam Kwong 19 4 0 04 Nov 2018
Minimax Estimation of Neural Net Distance Kaiyi Ji Yingbin Liang GAN 22 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 29 8 0 01 Nov 2018
A Priori Estimates of the Population Risk for Two-layer Neural Networks Weinan E Chao Ma Lei Wu 29 130 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 23 245 0 12 Oct 2018
Detecting Memorization in ReLU Networks Edo Collins Siavash Bigdeli Sabine Süsstrunk 36 4 0 08 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 44 191 0 02 Oct 2018
Predicting the Generalization Gap in Deep Networks with Margin Distributions Yiding Jiang Dilip Krishnan H. Mobahi Samy Bengio UQCV 26 198 0 28 Sep 2018
Fluctuation-dissipation relations for stochastic gradient descent Sho Yaida 32 73 0 28 Sep 2018
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust Bo Han Gang Niu Xingrui Yu Quanming Yao Miao Xu Ivor Tsang Masashi Sugiyama NoLa 17 7 0 28 Sep 2018
On the loss landscape of a class of deep neural networks with no bad local valleys Quynh N. Nguyen Mahesh Chandra Mukkamala Matthias Hein 16 87 0 27 Sep 2018
Identifying Generalization Properties in Neural Networks Huan Wang N. Keskar Caiming Xiong R. Socher 6 49 0 19 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
Approximation and Estimation for High-Dimensional Deep Learning Networks Andrew R. Barron Jason M. Klusowski 27 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 14 181 0 09 Sep 2018
Generalisation in humans and deep neural networks Robert Geirhos Carlos R. Medina Temme Jonas Rauber Heiko H. Schutt Matthias Bethge Felix Wichmann OOD 40 598 0 27 Aug 2018
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization G. Wang G. Giannakis Jie Chen MLT 24 131 0 14 Aug 2018
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 32 109 0 03 Aug 2018
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length Stanislaw Jastrzebski Zachary Kenton Nicolas Ballas Asja Fischer Yoshua Bengio Amos Storkey ODL 23 114 0 13 Jul 2018
A Mean-Field Optimal Control Formulation of Deep Learning Weinan E Jiequn Han Qianxiao Li OOD 14 181 0 03 Jul 2018
Theory IIIb: Generalization in Deep Networks T. Poggio Q. Liao Brando Miranda Andrzej Banburski Xavier Boix Jack Hidary ODL AI4CE 32 26 0 29 Jun 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 57 1,394 0 22 Jun 2018
Built-in Vulnerabilities to Imperceptible Adversarial Perturbations T. Tanay Jerone T. A. Andrews Lewis D. Griffin 18 7 0 19 Jun 2018
Detecting Dead Weights and Units in Neural Networks Utku Evci CVBM 27 7 0 15 Jun 2018
PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments Anirudha Majumdar M. Goldstein Anoopkumar Sonar 23 18 0 11 Jun 2018
Implicit regularization and solution uniqueness in over-parameterized matrix sensing Kelly Geyer Anastasios Kyrillidis A. Kalev 27 4 0 06 Jun 2018
Minnorm training: an algorithm for training over-parameterized deep neural networks Yamini Bansal Madhu S. Advani David D. Cox Andrew M. Saxe ODL 15 18 0 03 Jun 2018
Understanding Batch Normalization Johan Bjorck Carla P. Gomes B. Selman Kilian Q. Weinberger 21 593 0 01 Jun 2018
Automated proof synthesis for propositional logic with deep neural networks Taro Sekiyama Kohei Suenaga NAI 14 10 0 30 May 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 19 516 0 28 May 2018
Deep learning generalizes because the parameter-function map is biased towards simple functions Guillermo Valle Pérez Chico Q. Camargo A. Louis MLT AI4CE 18 225 0 22 May 2018
Deep Learning with Cinematic Rendering: Fine-Tuning Deep Neural Networks Using Photorealistic Medical Images Faisal Mahmood Richard J. Chen S. Sudarsky Daphne Yu Nicholas J. Durr MedIm 19 43 0 22 May 2018
DNN or k-NN: That is the Generalize vs. Memorize Question Gilad Cohen Guillermo Sapiro Raja Giryes 19 38 0 17 May 2018
A Study on Overfitting in Deep Reinforcement Learning Chiyuan Zhang Oriol Vinyals Rémi Munos Samy Bengio OffRL OnRL 18 384 0 18 Apr 2018
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach Wenda Zhou Victor Veitch Morgane Austern Ryan P. Adams Peter Orbanz 44 209 0 16 Apr 2018
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds Cenk Baykal Lucas Liebenwein Igor Gilitschenski Dan Feldman Daniela Rus 25 79 0 15 Apr 2018
Adversarial Training Versus Weight Decay A. Galloway T. Tanay Graham W. Taylor AAML 27 23 0 10 Apr 2018
Information Theoretic Interpretation of Deep learning Tianchen Zhao FAtt 20 2 0 21 Mar 2018
Assessing Shape Bias Property of Convolutional Neural Networks Hossein Hosseini Baicen Xiao Mayoore S. Jaiswal Radha Poovendran 8 36 0 21 Mar 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 18 328 0 19 Mar 2018
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs Diviyan Kalainathan Olivier Goudet Isabelle M Guyon David Lopez-Paz Michèle Sebag CML 26 93 0 13 Mar 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du J. Lee 27 267 0 03 Mar 2018
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects Zhanxing Zhu Jingfeng Wu Ting Yu Lei Wu Jin Ma 11 40 0 01 Mar 2018
A Walk with SGD Chen Xing Devansh Arpit Christos Tsirigotis Yoshua Bengio 27 118 0 24 Feb 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak Yasaman Bahri Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein AAML 18 436 0 23 Feb 2018
An analysis of training and generalization errors in shallow and deep networks H. Mhaskar T. Poggio UQCV 30 18 0 17 Feb 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 26 630 0 14 Feb 2018
A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization Tianyi Liu Zhehui Chen Enlu Zhou T. Zhao 22 14 0 14 Feb 2018
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent Yifan Wu Barnabás Póczós Aarti Singh MLT 27 8 0 13 Feb 2018