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"

44 / 44 papers shown

Title
Paint Outside the Box: Synthesizing and Selecting Training Data for Visual Grounding Zilin Du Haoxin Li Jianfei Yu Boyang Li 132 0 0 01 Dec 2024
Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods Hossein Taheri Christos Thrampoulidis Arya Mazumdar MLT 31 0 0 13 Oct 2024
Training on Synthetic Data Beats Real Data in Multimodal Relation Extraction Zilin Du Haoxin Li Xu Guo Boyang Li 29 1 0 05 Dec 2023
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning Jing Zhu Xiang Song V. Ioannidis Danai Koutra Christos Faloutsos 54 13 0 25 Sep 2023
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics Yehonatan Avidan Qianyi Li H. Sompolinsky 60 8 0 08 Sep 2023
Double Descent of Discrepancy: A Task-, Data-, and Model-Agnostic Phenomenon Yi-Xiao Luo Bin Dong 26 0 0 25 May 2023
Learning with Noisy Labels through Learnable Weighting and Centroid Similarity F. Wani Maria Sofia Bucarelli Fabrizio Silvestri NoLa 29 3 0 16 Mar 2023
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 30 11 0 15 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 20 6 0 02 Nov 2022
Automatic Data Augmentation via Invariance-Constrained Learning Ignacio Hounie Luiz F. O. Chamon Alejandro Ribeiro 18 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 35 27 0 20 Sep 2022
On the Activation Function Dependence of the Spectral Bias of Neural Networks Q. Hong Jonathan W. Siegel Qinyan Tan Jinchao Xu 32 22 0 09 Aug 2022
Sparse Double Descent: Where Network Pruning Aggravates Overfitting Zhengqi He Zeke Xie Quanzhi Zhu Zengchang Qin 67 27 0 17 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 19 9 0 04 Jun 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 27 29 0 15 Feb 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers Deebul Nair Nico Hochgeschwender Miguel A. Olivares-Mendez OOD 22 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 Mingming Gong Tongliang Liu NoLa 33 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 25 64 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 28 72 0 11 Jan 2022
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 13 21 0 15 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 27 16 0 05 Dec 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 25 19 0 09 Nov 2021
Subquadratic Overparameterization for Shallow Neural Networks Chaehwan Song Ali Ramezani-Kebrya Thomas Pethick Armin Eftekhari V. Cevher 22 31 0 02 Nov 2021
Mitigating Memorization of Noisy Labels via Regularization between Representations Hao Cheng Zhaowei Zhu Xing Sun Yang Liu NoLa 33 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 71 17 0 16 Oct 2021
Robustness and Reliability When Training With Noisy Labels Amanda Olmin Fredrik Lindsten OOD NoLa 16 14 0 07 Oct 2021
Learning with Noisy Labels via Sparse Regularization Xiong Zhou Xianming Liu Chenyang Wang Deming Zhai Junjun Jiang Xiangyang Ji NoLa 26 51 0 31 Jul 2021
A Theoretical Analysis of Fine-tuning with Linear Teachers Gal Shachaf Alon Brutzkus Amir Globerson 26 17 0 04 Jul 2021
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion Xian-Jin Gui Wei Wang Zhang-Hao Tian NoLa 22 44 0 17 Jun 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization Saurabh Garg Sivaraman Balakrishnan J. Zico Kolter Zachary Chase Lipton 25 29 0 01 May 2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split Samet Oymak Mingchen Li Mahdi Soltanolkotabi AI4CE OOD 28 13 0 29 Apr 2021
Provable Super-Convergence with a Large Cyclical Learning Rate Samet Oymak 25 12 0 22 Feb 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 27 2 0 04 Jan 2021
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 24 158 0 09 Nov 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 22 79 0 17 Sep 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip H. S. Torr NoLa AAML 23 57 0 08 Jul 2020
Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent Mehdi Abbana Bennani Thang Doan Masashi Sugiyama CLL 42 61 0 21 Jun 2020
When Does Preconditioning Help or Hurt Generalization? S. Amari Jimmy Ba Roger C. Grosse Xuechen Li Atsushi Nitanda Taiji Suzuki Denny Wu Ji Xu 26 32 0 18 Jun 2020
Part-dependent Label Noise: Towards Instance-dependent Label Noise Xiaobo Xia Tongliang Liu Bo Han Nannan Wang Mingming Gong Haifeng Liu Gang Niu Dacheng Tao Masashi Sugiyama NoLa 6 67 0 14 Jun 2020
LOCA: LOcal Conformal Autoencoder for standardized data coordinates Erez Peterfreund Ofir Lindenbaum Felix Dietrich Tom S. Bertalan M. Gavish Ioannis G. Kevrekidis Ronald R. Coifman 71 22 0 15 Apr 2020
Learning Not to Learn in the Presence of Noisy Labels Liu Ziyin Blair Chen Ru Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda NoLa 16 18 0 16 Feb 2020
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators Reinhard Heckel Mahdi Soltanolkotabi DiffM 27 81 0 31 Oct 2019
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,886 0 15 Sep 2016