On the Role of Label Noise in the Feature Learning Process

25 May 2025

Papers citing "On the Role of Label Noise in the Feature Learning Process"

46 / 46 papers shown

Title
CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation Bowen Song Zecheng Zhang Zhaoxu Luo Jason Hu Wei Yuan Jing Jia Zhengxu Tang Guanyang Wang Liyue Shen DiffM 45 3 0 07 Feb 2025
On the Comparison between Multi-modal and Single-modal Contrastive Learning Wei Huang Andi Han Yongqiang Chen Yuan Cao Zhiqiang Xu Taiji Suzuki 24 6 0 05 Nov 2024
Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes Zhenfeng Tu Santiago Aranguri Arthur Jacot 40 10 0 27 May 2024
Why Does Sharpness-Aware Minimization Generalize Better Than SGD? Zixiang Chen Junkai Zhang Yiwen Kou Xiangning Chen Cho-Jui Hsieh Quanquan Gu 69 15 0 11 Oct 2023
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data Zhiwei Xu Yutong Wang Spencer Frei Gal Vardi Wei Hu MLT 56 27 0 04 Oct 2023
Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data Xuran Meng Difan Zou Yuan Cao MLT 76 9 0 03 Oct 2023
Regularly Truncated M-estimators for Learning with Noisy Labels Xiaobo Xia Pengqian Lu Chen Gong Bo Han Jun-chen Yu Jun Yu Tongliang Liu NoLa 52 11 0 02 Sep 2023
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective Wei Huang Yuanbin Cao Hong Wang Xin Cao Taiji Suzuki MLT 58 8 0 24 Jun 2023
On Emergence of Clean-Priority Learning in Early Stopped Neural Networks Chaoyue Liu Amirhesam Abedsoltan M. Belkin NoLa 45 5 0 05 Jun 2023
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels Jian Chen Ruiyi Zhang Tong Yu Rohan Sharma Zhiqiang Xu Tong Sun Changyou Chen DiffM 59 19 0 31 May 2023
Understanding and Improving Feature Learning for Out-of-Distribution Generalization Yongqiang Chen Wei Huang Kaiwen Zhou Yatao Bian Bo Han James Cheng MLT OOD OODD 34 27 0 22 Apr 2023
The Benefits of Mixup for Feature Learning Difan Zou Yuan Cao Yuan-Fang Li Quanquan Gu MLT 16 20 0 15 Mar 2023
Benign Overfitting for Two-layer ReLU Convolutional Neural Networks Yiwen Kou Zi-Yuan Chen Yuanzhou Chen Quanquan Gu MLT 60 16 0 07 Mar 2023
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity Hongkang Li Ming Wang Sijia Liu Pin-Yu Chen ViT MLT 62 59 0 12 Feb 2023
Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup Muthuraman Chidambaram Xiang Wang Chenwei Wu Rong Ge MLT 44 9 0 24 Oct 2022
On Feature Learning in the Presence of Spurious Correlations Pavel Izmailov Polina Kirichenko Nate Gruver A. Wilson 66 126 0 20 Oct 2022
Vision Transformers provably learn spatial structure Samy Jelassi Michael E. Sander Yuan-Fang Li ViT MLT 44 78 0 13 Oct 2022
Towards understanding how momentum improves generalization in deep learning Samy Jelassi Yuanzhi Li ODL MLT AI4CE 45 35 0 13 Jul 2022
Neural Networks can Learn Representations with Gradient Descent Alexandru Damian Jason D. Lee Mahdi Soltanolkotabi SSL MLT 74 115 0 30 Jun 2022
Benign Overfitting in Two-layer Convolutional Neural Networks Yuan Cao Zixiang Chen M. Belkin Quanquan Gu MLT 41 88 0 14 Feb 2022
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 51 72 0 11 Feb 2022
Salient ImageNet: How to discover spurious features in Deep Learning? Sahil Singla Soheil Feizi AAML VLM 47 117 0 08 Oct 2021
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization Difan Zou Yuan Cao Yuanzhi Li Quanquan Gu MLT AI4CE 77 41 0 25 Aug 2021
Understanding and Improving Early Stopping for Learning with Noisy Labels Ying-Long Bai Erkun Yang Bo Han Yanhua Yang Jiatong Li Yinian Mao Gang Niu Tongliang Liu NoLa 33 216 0 30 Jun 2021
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise Spencer Frei Yuan Cao Quanquan Gu FedML MLT 81 21 0 04 Jan 2021
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning Zeyuan Allen-Zhu Yuanzhi Li FedML 100 362 0 17 Dec 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 64 561 0 30 Jun 2020
The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks Wei Hu Lechao Xiao Ben Adlam Jeffrey Pennington 36 63 0 25 Jun 2020
When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari 74 188 0 24 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 59 149 0 20 May 2020
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 172 375 0 09 May 2020
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks Yuanzhi Li Colin Wei Tengyu Ma 32 295 0 10 Jul 2019
Kernel and Rich Regimes in Overparametrized Models Blake E. Woodworth Suriya Gunasekar Pedro H. P. Savarese E. Moroshko Itay Golan Jason D. Lee Daniel Soudry Nathan Srebro 61 358 0 13 Jun 2019
SGD on Neural Networks Learns Functions of Increasing Complexity Preetum Nakkiran Gal Kaplun Dimitris Kalimeris Tristan Yang Benjamin L. Edelman Fred Zhang Boaz Barak MLT 124 242 0 28 May 2019
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks Mingchen Li Mahdi Soltanolkotabi Samet Oymak NoLa 91 352 0 27 Mar 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 108 966 0 24 Jan 2019
How does Disagreement Help Generalization against Label Corruption? Xingrui Yu Bo Han Jiangchao Yao Gang Niu Ivor W. Tsang Masashi Sugiyama NoLa 37 778 0 14 Jan 2019
On Lazy Training in Differentiable Programming Lénaïc Chizat Edouard Oyallon Francis R. Bach 82 823 0 19 Dec 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 159 3,160 0 20 Jun 2018
Dimensionality-Driven Learning with Noisy Labels Xingjun Ma Yisen Wang Michael E. Houle Shuo Zhou S. Erfani Shutao Xia S. Wijewickrema James Bailey NoLa 55 429 0 07 Jun 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han Quanming Yao Xingrui Yu Gang Niu Miao Xu Weihua Hu Ivor Tsang Masashi Sugiyama NoLa 82 2,051 0 18 Apr 2018
Joint Optimization Framework for Learning with Noisy Labels Daiki Tanaka Daiki Ikami T. Yamasaki Kiyoharu Aizawa NoLa 58 708 0 30 Mar 2018
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 95 1,801 0 16 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 452 21,459 0 22 May 2017
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach Giorgio Patrini A. Rozza A. Menon Richard Nock Zhuang Li NoLa 83 1,444 0 13 Sep 2016
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 860 99,991 0 04 Sep 2014