Understanding deep learning requires rethinking generalization

10 November 2016

Benjamin Recht

Papers citing "Understanding deep learning requires rethinking generalization"

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Title
From Variational to Deterministic Autoencoders Partha Ghosh Mehdi S. M. Sajjadi Antonio Vergari Michael J. Black Bernhard Schölkopf DRL 34 269 0 29 Mar 2019
IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude's Variance Matters Xinshao Wang Yang Hua Elyor Kodirov David A. Clifton N. Robertson NoLa 24 62 0 28 Mar 2019
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks Mingchen Li Mahdi Soltanolkotabi Samet Oymak NoLa 47 351 0 27 Mar 2019
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels Kun Yi Jianxin Wu NoLa 36 409 0 19 Mar 2019
An Effective Label Noise Model for DNN Text Classification Ishan Jindal Daniel Pressel Brian Lester M. Nokleby NoLa 32 48 0 18 Mar 2019
Deep learning observables in computational fluid dynamics K. Lye Siddhartha Mishra Deep Ray OOD AI4CE 15 158 0 07 Mar 2019
Calibration of Encoder Decoder Models for Neural Machine Translation Aviral Kumar Sunita Sarawagi 16 98 0 03 Mar 2019
Unsupervised Tracklet Person Re-Identification Minxian Li Xiatian Zhu S. Gong 23 171 0 01 Mar 2019
Deep learning in bioinformatics: introduction, application, and perspective in big data era Yu Li Chao Huang Lizhong Ding Zhongxiao Li Yijie Pan Xin Gao AI4CE 21 295 0 28 Feb 2019
Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers Baihan Lin 16 2 0 27 Feb 2019
Adaptive Estimators Show Information Compression in Deep Neural Networks Ivan Chelombiev Conor J. Houghton Cian O’Donnell 16 34 0 24 Feb 2019
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization Hesham Mostafa Xin Wang 34 307 0 15 Feb 2019
Error Feedback Fixes SignSGD and other Gradient Compression Schemes Sai Praneeth Karimireddy Quentin Rebjock Sebastian U. Stich Martin Jaggi 18 493 0 28 Jan 2019
Stiffness: A New Perspective on Generalization in Neural Networks Stanislav Fort Pawel Krzysztof Nowak Stanislaw Jastrzebski S. Narayanan 19 94 0 28 Jan 2019
Augment your batch: better training with larger batches Elad Hoffer Tal Ben-Nun Itay Hubara Niv Giladi Torsten Hoefler Daniel Soudry ODL 27 72 0 27 Jan 2019
Challenges in Designing Datasets and Validation for Autonomous Driving Michal Uřičář David Hurych P. Krízek S. Yogamani 20 34 0 26 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 37 961 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 19 54 0 24 Jan 2019
Traditional and Heavy-Tailed Self Regularization in Neural Network Models Charles H. Martin Michael W. Mahoney 21 119 0 24 Jan 2019
Robust Learning at Noisy Labeled Medical Images: Applied to Skin Lesion Classification Cheng Xue Qi Dou Xueying Shi Hao Chen Pheng Ann Heng NoLa 13 104 0 23 Jan 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 20 237 0 18 Jan 2019
Domain Adaptation for Structured Output via Discriminative Patch Representations Yi-Hsuan Tsai Kihyuk Sohn S. Schulter Manmohan Chandraker OOD 38 319 0 16 Jan 2019
Deep Learning for Human Affect Recognition: Insights and New Developments Philipp V. Rouast M. Adam R. Chiong 32 167 0 09 Jan 2019
Scaling description of generalization with number of parameters in deep learning Mario Geiger Arthur Jacot S. Spigler Franck Gabriel Levent Sagun Stéphane dÁscoli Giulio Biroli Clément Hongler M. Wyart 49 195 0 06 Jan 2019
SGD Converges to Global Minimum in Deep Learning via Star-convex Path Yi Zhou Junjie Yang Huishuai Zhang Yingbin Liang Vahid Tarokh 14 71 0 02 Jan 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 45 1,610 0 28 Dec 2018
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology Bastian Alexander Rieck Matteo Togninalli Christian Bock Michael Moor Max Horn Thomas Gumbsch Karsten M. Borgwardt 20 111 0 23 Dec 2018
Entropy-Constrained Training of Deep Neural Networks Simon Wiedemann Arturo Marbán K. Müller Wojciech Samek 22 27 0 18 Dec 2018
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks Henning Petzka C. Sminchisescu 27 9 0 16 Dec 2018
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 46 712 0 12 Dec 2018
On the potential for open-endedness in neural networks N. Guttenberg N. Virgo A. Penn 21 10 0 12 Dec 2018
Gradient Descent Happens in a Tiny Subspace Guy Gur-Ari Daniel A. Roberts Ethan Dyer 28 228 0 12 Dec 2018
Regularization by architecture: A deep prior approach for inverse problems Sören Dittmer T. Kluth Peter Maass Daniel Otero Baguer 35 97 0 10 Dec 2018
Three Tools for Practical Differential Privacy K. V. D. Veen Ruben Seggers Peter Bloem Giorgio Patrini 19 39 0 07 Dec 2018
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV AAML 13 243 0 03 Dec 2018
Towards Theoretical Understanding of Large Batch Training in Stochastic Gradient Descent Xiaowu Dai Yuhua Zhu 25 11 0 03 Dec 2018
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 134 186 0 02 Dec 2018
Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks Drew Linsley Junkyung Kim D. Berson Thomas Serre 3DV 30 17 0 28 Nov 2018
Learning Sound Events From Webly Labeled Data Anurag Kumar Ankit Parag Shah Bhiksha Raj Alexander G. Hauptmann NoLa 29 12 0 25 Nov 2018
Limited Gradient Descent: Learning With Noisy Labels Yi Sun Yan Tian Yiping Xu Jianxiang Li NoLa 35 13 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 16 271 0 19 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 396 0 19 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du J. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 41 1,122 0 09 Nov 2018
Statistical Characteristics of Deep Representations: An Empirical Investigation Daeyoung Choi Kyungeun Lee Changho Shin Stephen J. Roberts AI4TS 16 2 0 08 Nov 2018
Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications Deren Lei Zichen Sun Yijun Xiao William Yang Wang 33 14 0 01 Nov 2018
Analyzing biological and artificial neural networks: challenges with opportunities for synergy? David Barrett Ari S. Morcos Jakob H. Macke AI4CE 25 110 0 31 Oct 2018
On the Convergence Rate of Training Recurrent Neural Networks Zeyuan Allen-Zhu Yuanzhi Li Zhao Song 18 191 0 29 Oct 2018
Applying Deep Learning To Airbnb Search Malay Haldar Mustafa Abdool Prashant Ramanathan Tao Xu Shulin Yang ... Qing Zhang Nick Barrow-Williams B. Turnbull Brendan M. Collins Thomas Legrand DML 23 83 0 22 Oct 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 23 117 0 17 Oct 2018
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani Francis R. Bach Mark W. Schmidt 30 296 0 16 Oct 2018