Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks

27 March 2019

Papers citing "Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks"

50 / 176 papers shown

Title
Combining Self-labeling with Selective Sampling Jedrzej Kozal Michal Wo'zniak 26 3 0 11 Jan 2023
PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels Huaxi Huang Hui-Sung Kang Sheng Liu Olivier Salvado Thierry Rakotoarivelo Dadong Wang Tongliang Liu NoLa 25 7 0 07 Dec 2022
Margin-based sampling in high dimensions: When being active is less efficient than staying passive A. Tifrea Jacob Clarysse Fanny Yang 27 2 0 01 Dec 2022
Noisy Pairing and Partial Supervision for Opinion Summarization Hayate Iso Xiaolan Wang Yoshihiko Suhara AI4TS 13 0 0 16 Nov 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 38 11 0 15 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
Deep Learning is Provably Robust to Symmetric Label Noise Carey E. Priebe Ningyuan Huang Soledad Villar Cong Mu Li-Wei Chen NoLa 21 2 0 26 Oct 2022
Automatic Data Augmentation via Invariance-Constrained Learning Ignacio Hounie Luiz F. O. Chamon Alejandro Ribeiro 23 10 0 29 Sep 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics Shoaib Ahmed Siddiqui Nitarshan Rajkumar Tegan Maharaj David M. Krueger Sara Hooker 42 27 0 20 Sep 2022
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks Yunwen Lei Rong Jin Yiming Ying MLT 37 18 0 19 Sep 2022
Intersection of Parallels as an Early Stopping Criterion Ali Vardasbi Maarten de Rijke Mostafa Dehghani MoMe 38 5 0 19 Aug 2022
Labeling Chaos to Learning Harmony: Federated Learning with Noisy Labels Vasileios Tsouvalas Aaqib Saeed T. Ozcelebi N. Meratnia FedML 25 12 0 19 Aug 2022
CTRL: Clustering Training Losses for Label Error Detection C. Yue N. Jha NoLa 41 14 0 17 Aug 2022
On the Activation Function Dependence of the Spectral Bias of Neural Networks Q. Hong Jonathan W. Siegel Qinyan Tan Jinchao Xu 34 23 0 09 Aug 2022
MarkerMap: nonlinear marker selection for single-cell studies Nabeel Sarwar Wilson Gregory George A. Kevrekidis Soledad Villar Bianca Dumitrascu 6 4 0 28 Jul 2022
Identifying Hard Noise in Long-Tailed Sample Distribution Xuanyu Yi Kaihua Tang Xiansheng Hua J. Lim Hanwang Zhang 22 23 0 27 Jul 2022
ProMix: Combating Label Noise via Maximizing Clean Sample Utility Rui Xiao Yiwen Dong Haobo Wang Lei Feng Runze Wu Gang Chen J. Zhao 24 54 0 21 Jul 2022
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets Yingsong Huang Bing Bai Shengwei Zhao Kun Bai Fei-Yue Wang NoLa 28 43 0 12 Jul 2022
Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale A. Veldanda Ivan Brugere Jiahao Chen Sanghamitra Dutta Alan Mishler S. Garg 33 7 0 29 Jun 2022
Sparse Double Descent: Where Network Pruning Aggravates Overfitting Zhengqi He Zeke Xie Quanzhi Zhu Zengchang Qin 74 27 0 17 Jun 2022
Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime Benjamin Bowman Guido Montúfar 22 14 0 06 Jun 2022
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees Haotian Ju Dongyue Li Hongyang R. Zhang 43 28 0 06 Jun 2022
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile Dong Chen Lingfei Wu Siliang Tang Xiao Yun Bo Long Yueting Zhuang VLM NoLa 25 9 0 04 Jun 2022
Towards a Defense Against Federated Backdoor Attacks Under Continuous Training Shuai Wang J. Hayase Giulia Fanti Sewoong Oh FedML 23 5 0 24 May 2022
AdaCap: Adaptive Capacity control for Feed-Forward Neural Networks Katia Méziani Karim Lounici Benjamin Riu 6 0 0 09 May 2022
On Learning Contrastive Representations for Learning with Noisy Labels Linya Yi Sheng Liu Qi She A. McLeod Boyu Wang NoLa 16 40 0 03 Mar 2022
Robust Training under Label Noise by Over-parameterization Sheng Liu Zhihui Zhu Qing Qu Chong You NoLa OOD 27 106 0 28 Feb 2022
Explicit Regularization via Regularizer Mirror Descent Navid Azizan Sahin Lale B. Hassibi 12 4 0 22 Feb 2022
On Optimal Early Stopping: Over-informative versus Under-informative Parametrization Ruoqi Shen Liyao (Mars) Gao Yi Ma 14 13 0 20 Feb 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 30 29 0 15 Feb 2022
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression Jing Xu Jiaye Teng Yang Yuan Andrew Chi-Chih Yao 23 1 0 12 Feb 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers Deebul Nair Nico Hochgeschwender Miguel A. Olivares-Mendez OOD 30 7 0 03 Feb 2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise? Yexiong Lin Yu Yao Yuxuan Du Jun Yu Bo Han Biwei Huang Tongliang Liu NoLa 53 3 0 30 Jan 2022
A Stochastic Bundle Method for Interpolating Networks Alasdair Paren Leonard Berrada Rudra P. K. Poudel M. P. Kumar 24 4 0 29 Jan 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 33 66 0 19 Jan 2022
In Defense of the Unitary Scalarization for Deep Multi-Task Learning Vitaly Kurin Alessandro De Palma Ilya Kostrikov Shimon Whiteson M. P. Kumar 39 73 0 11 Jan 2022
Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture Zihao Deng Zee Fryer Brendan Juba Rina Panigrahy Xin Wang 14 2 0 21 Dec 2021
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 24 21 0 15 Dec 2021
Robust Neural Network Classification via Double Regularization Olof Zetterqvist Rebecka Jörnsten J. Jonasson 9 1 0 15 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 38 16 0 05 Dec 2021
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection Seong Min Kye Kwanghee Choi Joonyoung Yi Buru Chang NoLa 33 15 0 29 Nov 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 29 19 0 09 Nov 2021
Subquadratic Overparameterization for Shallow Neural Networks Chaehwan Song Ali Ramezani-Kebrya Thomas Pethick Armin Eftekhari V. Cevher 27 31 0 02 Nov 2021
Mitigating Memorization of Noisy Labels via Regularization between Representations Hao Cheng Zhaowei Zhu Xing Sun Yang Liu NoLa 38 28 0 18 Oct 2021
Pro-KD: Progressive Distillation by Following the Footsteps of the Teacher Mehdi Rezagholizadeh A. Jafari Puneeth Salad Pranav Sharma Ali Saheb Pasand A. Ghodsi 79 17 0 16 Oct 2021
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 149 62 0 12 Oct 2021
Robustness and Reliability When Training With Noisy Labels Amanda Olmin Fredrik Lindsten OOD NoLa 16 14 0 07 Oct 2021
Consistency Regularization Can Improve Robustness to Label Noise Erik Englesson Hossein Azizpour NoLa 97 20 0 04 Oct 2021
When are Deep Networks really better than Decision Forests at small sample sizes, and how? Haoyin Xu K. A. Kinfu Will LeVine Sambit Panda Jayanta Dey ... M. Kusmanov F. Engert Christopher M. White Joshua T. Vogelstein Carey E. Priebe 17 23 0 31 Aug 2021
Heavy-tailed Streaming Statistical Estimation Che-Ping Tsai Adarsh Prasad Sivaraman Balakrishnan Pradeep Ravikumar 28 10 0 25 Aug 2021