Understanding deep learning requires rethinking generalization

10 November 2016

Benjamin Recht

Papers citing "Understanding deep learning requires rethinking generalization"

50 / 1,076 papers shown

Title
Dynamic Hard Pruning of Neural Networks at the Edge of the Internet Lorenzo Valerio F. M. Nardini A. Passarella R. Perego 25 12 0 17 Nov 2020
Chaos and Complexity from Quantum Neural Network: A study with Diffusion Metric in Machine Learning S. Choudhury Ankan Dutta Debisree Ray 22 21 0 16 Nov 2020
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting Zeke Xie Fengxiang He Shaopeng Fu Issei Sato Dacheng Tao Masashi Sugiyama 21 60 0 12 Nov 2020
A Survey of Label-noise Representation Learning: Past, Present and Future Bo Han Quanming Yao Tongliang Liu Gang Niu Ivor W. Tsang James T. Kwok Masashi Sugiyama NoLa 24 159 0 09 Nov 2020
Teaching with Commentaries Aniruddh Raghu M. Raghu Simon Kornblith David Duvenaud Geoffrey E. Hinton 29 24 0 05 Nov 2020
Generalized Negative Correlation Learning for Deep Ensembling Sebastian Buschjäger Lukas Pfahler K. Morik FedML BDL UQCV 17 17 0 05 Nov 2020
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate Jingfeng Wu Difan Zou Vladimir Braverman Quanquan Gu 23 18 0 04 Nov 2020
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition Ben Adlam Jeffrey Pennington UD 42 93 0 04 Nov 2020
Latent Causal Invariant Model Xinwei Sun Botong Wu Xiangyu Zheng Chang-Shu Liu Wei Chen Tao Qin Tie-Yan Liu OOD CML BDL 31 14 0 04 Nov 2020
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference Michael Lui Yavuz Yetim Özgür Özkan Zhuoran Zhao Shin-Yeh Tsai Carole-Jean Wu Mark Hempstead GNN BDL LRM 22 51 0 04 Nov 2020
Instance based Generalization in Reinforcement Learning Martín Bertrán Natalia Martínez Mariano Phielipp Guillermo Sapiro OffRL 40 16 0 02 Nov 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 44 24 0 27 Oct 2020
Deep Networks from the Principle of Rate Reduction Kwan Ho Ryan Chan Yaodong Yu Chong You Haozhi Qi John N. Wright Yi Ma 22 21 0 27 Oct 2020
Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models J. Rocks Pankaj Mehta 25 41 0 26 Oct 2020
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes Jinyuan Jia Binghui Wang Neil Zhenqiang Gong AAML 35 5 0 26 Oct 2020
An Investigation of how Label Smoothing Affects Generalization Blair Chen Liu Ziyin Zihao Wang Paul Pu Liang UQCV 21 17 0 23 Oct 2020
Deep Learning is Singular, and That's Good Daniel Murfet Susan Wei Biwei Huang Hui Li Jesse Gell-Redman T. Quella UQCV 29 26 0 22 Oct 2020
Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher Guangda Ji Zhanxing Zhu 59 42 0 20 Oct 2020
Anti-Distillation: Improving reproducibility of deep networks G. Shamir Lorenzo Coviello 48 20 0 19 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 41 48 0 19 Oct 2020
For self-supervised learning, Rationality implies generalization, provably Yamini Bansal Gal Kaplun Boaz Barak OOD SSL 65 22 0 16 Oct 2020
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers Preetum Nakkiran Behnam Neyshabur Hanie Sedghi OffRL 29 11 0 16 Oct 2020
Regularizing Neural Networks via Adversarial Model Perturbation Yaowei Zheng Richong Zhang Yongyi Mao AAML 30 95 0 10 Oct 2020
How Does Mixup Help With Robustness and Generalization? Linjun Zhang Zhun Deng Kenji Kawaguchi Amirata Ghorbani James Zou AAML 47 244 0 09 Oct 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan Kankanhalli AAML 47 269 0 05 Oct 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 127 1,286 0 03 Oct 2020
Deep learning for time series classification Hassan Ismail Fawaz BDL AI4TS 43 35 0 01 Oct 2020
Group Whitening: Balancing Learning Efficiency and Representational Capacity Lei Huang Yi Zhou Li Liu Fan Zhu Ling Shao 33 21 0 28 Sep 2020
Improved generalization by noise enhancement Takashi Mori Masahito Ueda 24 3 0 28 Sep 2020
Learning Optimal Representations with the Decodable Information Bottleneck Yann Dubois Douwe Kiela D. Schwab Ramakrishna Vedantam 31 43 0 27 Sep 2020
Small Data, Big Decisions: Model Selection in the Small-Data Regime J. Bornschein Francesco Visin Simon Osindero 21 36 0 26 Sep 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 32 306 0 24 Sep 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 54 429 0 22 Sep 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 33 133 0 22 Sep 2020
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot Jingtong Su Yihang Chen Tianle Cai Tianhao Wu Ruiqi Gao Liwei Wang Jason D. Lee 16 85 0 22 Sep 2020
GraphCrop: Subgraph Cropping for Graph Classification Yiwei Wang Wei Wang Keli Zhang Yujun Cai Bryan Hooi 25 57 0 22 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 31 11 0 21 Sep 2020
Scale-Localized Abstract Reasoning Yaniv Benny Niv Pekar Lior Wolf 28 61 0 20 Sep 2020
Counterfactual Explanation and Causal Inference in Service of Robustness in Robot Control Simón C. Smith S. Ramamoorthy 26 13 0 18 Sep 2020
MoPro: Webly Supervised Learning with Momentum Prototypes Junnan Li Caiming Xiong Guosheng Lin 26 95 0 17 Sep 2020
Analysis of Generalizability of Deep Neural Networks Based on the Complexity of Decision Boundary Shuyue Guan Murray H. Loew 30 25 0 16 Sep 2020
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup Jang-Hyun Kim Wonho Choo Hyun Oh Song AAML 30 382 0 15 Sep 2020
Manifold attack K. Tran Fred-Maurice Ngole-Mboula Jean-Luc Starck AAML OOD 23 0 0 13 Sep 2020
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification G. Liang Yu Zhang Xiaoqin Wang Nathan Jacobs UQCV 28 60 0 09 Sep 2020
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering Jingtao Ding Yuhan Quan Quanming Yao Yong Li Depeng Jin 19 97 0 07 Sep 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai Shengjie Luo Keyulu Xu Di He Tie-Yan Liu Liwei Wang GNN 32 160 0 07 Sep 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl Wenjie Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 21 215 0 04 Sep 2020
Learning explanations that are hard to vary Giambattista Parascandolo Alexander Neitz Antonio Orvieto Luigi Gresele Bernhard Schölkopf FAtt 29 179 0 01 Sep 2020
Predicting Training Time Without Training L. Zancato Alessandro Achille Avinash Ravichandran Rahul Bhotika Stefano Soatto 26 24 0 28 Aug 2020
Training Sparse Neural Networks using Compressed Sensing Jonathan W. Siegel Jianhong Chen Pengchuan Zhang Jinchao Xu 28 5 0 21 Aug 2020