Understanding deep learning requires rethinking generalization

10 November 2016

Benjamin Recht

Papers citing "Understanding deep learning requires rethinking generalization"

50 / 883 papers shown

Title
An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images B. Damodaran Rémi Flamary Vivien Seguy Nicolas Courty NoLa 26 39 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 35 190 0 02 Oct 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
On the Learning Dynamics of Deep Neural Networks Rémi Tachet des Combes Mohammad Pezeshki Samira Shabanian Aaron Courville Yoshua Bengio 16 38 0 18 Sep 2018
Deep learning for time series classification: a review Hassan Ismail Fawaz Germain Forestier J. Weber L. Idoumghar Pierre-Alain Muller AI4TS AI4CE 98 2,650 0 12 Sep 2018
Towards Understanding Regularization in Batch Normalization Ping Luo Xinjiang Wang Wenqi Shao Zhanglin Peng MLT AI4CE 23 179 0 04 Sep 2018
Targeted Nonlinear Adversarial Perturbations in Images and Videos R. Rey-de-Castro H. Rabitz AAML 16 10 0 27 Aug 2018
Kernel Flows: from learning kernels from data into the abyss H. Owhadi G. Yoo 18 88 0 13 Aug 2018
Understanding training and generalization in deep learning by Fourier analysis Zhi-Qin John Xu AI4CE 21 92 0 13 Aug 2018
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 32 109 0 03 Aug 2018
Measuring abstract reasoning in neural networks David Barrett Felix Hill Adam Santoro Ari S. Morcos Timothy Lillicrap OOD 19 355 0 11 Jul 2018
Troubling Trends in Machine Learning Scholarship Zachary Chase Lipton Jacob Steinhardt 21 288 0 09 Jul 2018
Efficient Decentralized Deep Learning by Dynamic Model Averaging Michael Kamp Linara Adilova Joachim Sicking Fabian Hüger Peter Schlicht Tim Wirtz Stefan Wrobel 32 128 0 09 Jul 2018
ResNet with one-neuron hidden layers is a Universal Approximator Hongzhou Lin Stefanie Jegelka 38 227 0 28 Jun 2018
Understanding Dropout as an Optimization Trick Sangchul Hahn Heeyoul Choi ODL 13 34 0 26 Jun 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min-Bin Lin Fred Hamprecht Yoshua Bengio Aaron Courville 57 1,390 0 22 Jun 2018
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning Amy Zhang Nicolas Ballas Joelle Pineau CLL OffRL 25 177 0 20 Jun 2018
Learning One-hidden-layer ReLU Networks via Gradient Descent Xiao Zhang Yaodong Yu Lingxiao Wang Quanquan Gu MLT 28 134 0 20 Jun 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 37 3,098 0 20 Jun 2018
Insights on representational similarity in neural networks with canonical correlation Ari S. Morcos M. Raghu Samy Bengio DRL 32 429 0 14 Jun 2018
The committee machine: Computational to statistical gaps in learning a two-layers neural network Benjamin Aubin Antoine Maillard Jean Barbier Florent Krzakala N. Macris Lenka Zdeborová 41 104 0 14 Jun 2018
Scalable Neural Network Compression and Pruning Using Hard Clustering and L1 Regularization Yibo Yang Nicholas Ruozzi Vibhav Gogate 21 2 0 14 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
Data augmentation instead of explicit regularization Alex Hernández-García Peter König 30 141 0 11 Jun 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 21 372 0 08 Jun 2018
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 59 116 0 07 Jun 2018
Dimensionality-Driven Learning with Noisy Labels Xingjun Ma Yisen Wang Michael E. Houle Shuo Zhou S. Erfani Shutao Xia S. Wijewickrema James Bailey NoLa 29 425 0 07 Jun 2018
Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization Navid Azizan B. Hassibi 16 61 0 04 Jun 2018
Understanding Batch Normalization Johan Bjorck Carla P. Gomes B. Selman Kilian Q. Weinberger 18 593 0 01 Jun 2018
Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization D. Kobak Jonathan Lomond Benoit Sanchez 30 89 0 28 May 2018
Investigating Label Noise Sensitivity of Convolutional Neural Networks for Fine Grained Audio Signal Labelling Rainer Kelz Gerhard Widmer NoLa 11 4 0 28 May 2018
Topological Data Analysis of Decision Boundaries with Application to Model Selection K. Ramamurthy Kush R. Varshney Krishnan Mody 17 40 0 25 May 2018
Adding One Neuron Can Eliminate All Bad Local Minima Shiyu Liang Ruoyu Sun J. Lee R. Srikant 29 89 0 22 May 2018
SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning W. Wen Yandan Wang Feng Yan Cong Xu Chunpeng Wu Yiran Chen H. Li 24 50 0 21 May 2018
Tropical Geometry of Deep Neural Networks Liwen Zhang Gregory Naitzat Lek-Heng Lim 27 136 0 18 May 2018
Mad Max: Affine Spline Insights into Deep Learning Randall Balestriero Richard Baraniuk AI4CE 31 78 0 17 May 2018
Learnable PINs: Cross-Modal Embeddings for Person Identity Arsha Nagrani Samuel Albanie Andrew Zisserman SSL 26 140 0 02 May 2018
Boosting Self-Supervised Learning via Knowledge Transfer M. Noroozi Ananth Vinjimoor Paolo Favaro Hamed Pirsiavash SSL 209 292 0 01 May 2018
SHADE: Information Based Regularization for Deep Learning Michael Blot Thomas Robert Nicolas Thome Matthieu Cord 32 12 0 29 Apr 2018
Measuring the Intrinsic Dimension of Objective Landscapes Chunyuan Li Heerad Farkhoor Rosanne Liu J. Yosinski 19 397 0 24 Apr 2018
Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment Masatoshi Tsuchiya 21 160 0 22 Apr 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han Quanming Yao Xingrui Yu Gang Niu Miao Xu Weihua Hu Ivor Tsang Masashi Sugiyama NoLa 58 2,027 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 38 209 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 19 79 0 15 Apr 2018
Analysis on the Nonlinear Dynamics of Deep Neural Networks: Topological Entropy and Chaos Husheng Li 17 11 0 03 Apr 2018
Joint Optimization Framework for Learning with Noisy Labels Daiki Tanaka Daiki Ikami T. Yamasaki Kiyoharu Aizawa NoLa 39 702 0 30 Mar 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 48 1,410 0 24 Mar 2018
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 26 283 0 19 Mar 2018
Comparing Dynamics: Deep Neural Networks versus Glassy Systems Marco Baity-Jesi Levent Sagun Mario Geiger S. Spigler Gerard Ben Arous C. Cammarota Yann LeCun M. Wyart Giulio Biroli AI4CE 33 113 0 19 Mar 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 13 328 0 19 Mar 2018