Understanding deep learning requires rethinking generalization

10 November 2016

Benjamin Recht

Papers citing "Understanding deep learning requires rethinking generalization"

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Title
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms A. Camuto George Deligiannidis Murat A. Erdogdu Mert Gurbuzbalaban Umut cSimcsekli Lingjiong Zhu 33 29 0 09 Jun 2021
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs Enyan Dai Charu C. Aggarwal Suhang Wang NoLa 27 114 0 08 Jun 2021
Encoding-dependent generalization bounds for parametrized quantum circuits Matthias C. Caro Elies Gil-Fuster Johannes Jakob Meyer Jens Eisert R. Sweke UQCV 21 101 0 07 Jun 2021
Antipodes of Label Differential Privacy: PATE and ALIBI Mani Malek Ilya Mironov Karthik Prasad I. Shilov Florian Tramèr 16 62 0 07 Jun 2021
On Memorization in Probabilistic Deep Generative Models G. V. D. Burg Christopher K. I. Williams TDI 25 59 0 06 Jun 2021
Towards an Understanding of Benign Overfitting in Neural Networks Zhu Li Zhi-Hua Zhou Arthur Gretton MLT 33 35 0 06 Jun 2021
AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks S. K. Roy Mercedes Eugenia Paoletti J. Haut S. Dubey Purushottam Kar A. Plaza B. B. Chaudhuri ODL 27 18 0 21 May 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey Anton Van Den Hengel 51 87 0 12 May 2021
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels Erik Englesson Hossein Azizpour NoLa 34 104 0 10 May 2021
Self-paced Resistance Learning against Overfitting on Noisy Labels Xiaoshuang Shi Zhenhua Guo Fuyong Xing Yun Liang Xiaofeng Zhu NoLa 21 20 0 07 May 2021
Membership Inference Attacks on Deep Regression Models for Neuroimaging Umang Gupta Dmitris Stripelis Pradeep Lam Paul M. Thompson J. Ambite Greg Ver Steeg MIACV FedML 29 32 0 06 May 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 40 196 0 06 May 2021
Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning Yuyang Gao Giorgio Ascoli Liang Zhao 27 4 0 05 May 2021
AdaBoost and robust one-bit compressed sensing Geoffrey Chinot Felix Kuchelmeister Matthias Löffler Sara van de Geer 35 5 0 05 May 2021
Poisoning the Unlabeled Dataset of Semi-Supervised Learning Nicholas Carlini AAML 164 68 0 04 May 2021
Black-Box Dissector: Towards Erasing-based Hard-Label Model Stealing Attack Yixu Wang Jie Li Hong Liu Yan Wang Yongjian Wu Feiyue Huang Rongrong Ji AAML 25 34 0 03 May 2021
Who's Afraid of Adversarial Transferability? Ziv Katzir Yuval Elovici SILM AAML 27 9 0 02 May 2021
Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise Andrea Castellani Sebastian Schmitt Barbara Hammer NoLa 38 18 0 01 May 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization Saurabh Garg Sivaraman Balakrishnan J. Zico Kolter Zachary Chase Lipton 32 30 0 01 May 2021
InfoNEAT: Information Theory-based NeuroEvolution of Augmenting Topologies for Side-channel Analysis R. Acharya F. Ganji Domenic Forte AAML 46 24 0 30 Apr 2021
MeerCRAB: MeerLICHT Classification of Real and Bogus Transients using Deep Learning Zafiirah Hosenie S. Bloemen P. Groot R. Lyon B. Scheers ... Vanessa McBride R. L. le Poole K. Paterson D. Pieterse P. Woudt 34 7 0 28 Apr 2021
If your data distribution shifts, use self-learning E. Rusak Steffen Schneider George Pachitariu L. Eck Peter V. Gehler Oliver Bringmann Wieland Brendel Matthias Bethge VLM OOD TTA 81 30 0 27 Apr 2021
Demystification of Few-shot and One-shot Learning I. Tyukin A. Gorban Muhammad H. Alkhudaydi Qinghua Zhou 21 13 0 25 Apr 2021
Intentional Deep Overfit Learning (IDOL): A Novel Deep Learning Strategy for Adaptive Radiation Therapy J. Chun Justin C. Park S. Olberg You Zhang D. Nguyen Jing Wang Jin Sung Kim Steve B. Jiang 38 21 0 23 Apr 2021
Learning from Noisy Labels for Entity-Centric Information Extraction Wenxuan Zhou Muhao Chen NoLa 12 65 0 17 Apr 2021
Generalization bounds via distillation Daniel J. Hsu Ziwei Ji Matus Telgarsky Lan Wang FedML 27 32 0 12 Apr 2021
The surprising impact of mask-head architecture on novel class segmentation Vighnesh Birodkar Zhichao Lu Siyang Li V. Rathod Jonathan Huang ISeg 36 27 0 01 Apr 2021
Learning from Noisy Labels via Dynamic Loss Thresholding Hao Yang Youzhi Jin Zi-Hua Li Deng-Bao Wang Lei Miao Xin Geng Min-Ling Zhang NoLa AI4CE 32 6 0 01 Apr 2021
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization Zeke Xie Li-xin Yuan Zhanxing Zhu Masashi Sugiyama 27 29 0 31 Mar 2021
Collaborative Label Correction via Entropy Thresholding Hao Wu Jiangchao Yao Jiajie Wang Yinru Chen Ya Zhang Yanfeng Wang NoLa 22 4 0 31 Mar 2021
Progressive Domain Expansion Network for Single Domain Generalization Lei Li Ke Gao Juan Cao Ziyao Huang Yepeng Weng Xiaoyue Mi Zhengze Yu Xiaoya Li Boyang Xia OOD AI4CE 27 159 0 30 Mar 2021
Robust Audio-Visual Instance Discrimination Pedro Morgado Ishan Misra Nuno Vasconcelos SSL 22 110 0 29 Mar 2021
AlignMixup: Improving Representations By Interpolating Aligned Features Shashanka Venkataramanan Ewa Kijak Laurent Amsaleg Yannis Avrithis WSOL 35 61 0 29 Mar 2021
Understanding the role of importance weighting for deep learning Da Xu Yuting Ye Chuanwei Ruan FAtt 39 43 0 28 Mar 2021
From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation Chen Li G. Lee OOD 17 81 0 27 Mar 2021
Jo-SRC: A Contrastive Approach for Combating Noisy Labels Yazhou Yao Zeren Sun Chuanyi Zhang Fumin Shen Qi Wu Jian Zhang Zhenmin Tang NoLa 33 133 0 24 Mar 2021
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search Changlin Li Tao Tang Guangrun Wang Jiefeng Peng Bing Wang Xiaodan Liang Xiaojun Chang ViT 48 105 0 23 Mar 2021
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? Antonio Emanuele Cinà Sebastiano Vascon Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo AAML 32 9 0 23 Mar 2021
The Low-Rank Simplicity Bias in Deep Networks Minyoung Huh H. Mobahi Richard Y. Zhang Brian Cheung Pulkit Agrawal Phillip Isola 30 110 0 18 Mar 2021
Gradient Projection Memory for Continual Learning Gobinda Saha Isha Garg Kaushik Roy VLM CLL 47 270 0 17 Mar 2021
Triplet-Watershed for Hyperspectral Image Classification Aditya Challa Sravan Danda B. Sagar Laurent Najman 21 5 0 17 Mar 2021
Is it enough to optimize CNN architectures on ImageNet? Lukas Tuggener Jürgen Schmidhuber Thilo Stadelmann 33 23 0 16 Mar 2021
Detecting Human-Object Interaction via Fabricated Compositional Learning Zhi Hou B. Yu Yu Qiao Xiaojiang Peng Dacheng Tao 35 96 0 15 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 35 412 0 14 Mar 2021
Intraclass clustering: an implicit learning ability that regularizes DNNs Simon Carbonnelle Christophe De Vleeschouwer 60 8 0 11 Mar 2021
Fair Mixup: Fairness via Interpolation Ching-Yao Chuang Youssef Mroueh 21 138 0 11 Mar 2021
Reframing Neural Networks: Deep Structure in Overcomplete Representations Calvin Murdock George Cazenavette Simon Lucey BDL 41 4 0 10 Mar 2021
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment F. Cordeiro Ragav Sachdeva Vasileios Belagiannis Ian Reid G. Carneiro NoLa 19 77 0 06 Mar 2021
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy Lucas Liebenwein Cenk Baykal Brandon Carter David K Gifford Daniela Rus AAML 40 71 0 04 Mar 2021
FSDR: Frequency Space Domain Randomization for Domain Generalization Jiaxing Huang Dayan Guan Aoran Xiao Shijian Lu 39 218 0 03 Mar 2021