DivideMix: Learning with Noisy Labels as Semi-supervised Learning

18 February 2020

Papers citing "DivideMix: Learning with Noisy Labels as Semi-supervised Learning"

50 / 173 papers shown

Title
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning Jun Shu Xiang Yuan Deyu Meng Zongben Xu 28 4 0 13 May 2023
Noisy Correspondence Learning with Meta Similarity Correction Haocheng Han Kaiyao Miao Qinghua Zheng Minnan Luo 19 28 0 13 Apr 2023
Learning with Noisy Labels through Learnable Weighting and Centroid Similarity F. Wani Maria Sofia Bucarelli Fabrizio Silvestri NoLa 31 3 0 16 Mar 2023
Latent Class-Conditional Noise Model Jiangchao Yao Bo Han Zhihan Zhou Ya-Qin Zhang Ivor W. Tsang NoLa BDL 30 8 0 19 Feb 2023
Learning from Noisy Labels with Decoupled Meta Label Purifier Yuanpeng Tu Boshen Zhang Yuxi Li Liang Liu Jian Li Yabiao Wang Chengjie Wang C. Zhao NoLa 38 27 0 14 Feb 2023
Improve Noise Tolerance of Robust Loss via Noise-Awareness Kehui Ding Jun Shu Deyu Meng Zongben Xu NoLa 19 5 0 18 Jan 2023
Enhancing Self-Training Methods Aswathnarayan Radhakrishnan Jim Davis Zachary Rabin Benjamin Lewis Matthew Scherreik R. Ilin 19 1 0 18 Jan 2023
FedDebug: Systematic Debugging for Federated Learning Applications Waris Gill A. Anwar Muhammad Ali Gulzar FedML 26 11 0 09 Jan 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach Cuong C. Nguyen Thanh-Toan Do G. Carneiro NoLa 23 0 0 04 Jan 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels Yikai Wang Yanwei Fu Xinwei Sun NoLa 52 8 0 02 Jan 2023
Learning Confident Classifiers in the Presence of Label Noise Asma Ahmed Hashmi Aigerim Zhumabayeva Nikita Kotelevskii A. Agafonov Mohammad Yaqub Maxim Panov Martin Takávc NoLa 58 2 0 02 Jan 2023
On-the-fly Denoising for Data Augmentation in Natural Language Understanding Tianqing Fang Wenxuan Zhou Fangyu Liu Hongming Zhang Yangqiu Song Muhao Chen 36 1 0 20 Dec 2022
Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features Qingrui Jia Xuhong Li Lei Yu Jiang Bian Penghao Zhao Shupeng Li Haoyi Xiong Dejing Dou NoLa 22 5 0 19 Dec 2022
Dist-PU: Positive-Unlabeled Learning from a Label Distribution Perspective Yunrui Zhao Qianqian Xu Yangbangyan Jiang Peisong Wen Qingming Huang 22 37 0 06 Dec 2022
CrossSplit: Mitigating Label Noise Memorization through Data Splitting Jihye Kim A. Baratin Yan Zhang Simon Lacoste-Julien NoLa 18 7 0 03 Dec 2022
Model and Data Agreement for Learning with Noisy Labels Yuhang Zhang Weihong Deng Xingchen Cui Yunfeng Yin Hongzhi Shi Dongchao Wen NoLa 24 5 0 02 Dec 2022
FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning Yulei Qin Xingyu Chen Chao Chen Yunhang Shen Bohan Ren Yun Gu Jie-jin Yang Chunhua Shen 39 4 0 01 Dec 2022
Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels Sumyeong Ahn Se-Young Yun NoLa 26 2 0 01 Dec 2022
On Robust Learning from Noisy Labels: A Permutation Layer Approach Salman Alsubaihi Mohammed Alkhrashi Raied Aljadaany Fahad Albalawi Bernard Ghanem NoLa 13 0 0 29 Nov 2022
Learning with Silver Standard Data for Zero-shot Relation Extraction Tianyi Wang Jianwei Wang Ziqian Zeng 21 2 0 25 Nov 2022
Learning with Partial Labels from Semi-supervised Perspective Ximing Li Yuanzhi Jiang C. Li Yiyuan Wang Jihong Ouyang SSL 21 15 0 24 Nov 2022
A Benchmark of Long-tailed Instance Segmentation with Noisy Labels Guanlin Li Guowen Xu Tianwei Zhang NoLa ISeg 16 0 0 24 Nov 2022
Robust Training for Speaker Verification against Noisy Labels Zhihua Fang Liang He Hanhan Ma Xiao-Min Guo Lin Li NoLa 22 3 0 22 Nov 2022
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method Manyi Zhang Xuyang Zhao Jun Yao Chun Yuan Weiran Huang 30 20 0 20 Nov 2022
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels Daehwan Kim Kwang-seok Ryoo Hansang Cho Seung Wook Kim NoLa 24 3 0 20 Nov 2022
Learning from Long-Tailed Noisy Data with Sample Selection and Balanced Loss Lefan Zhang Zhang-Hao Tian Wujun Zhou W. Wang NoLa 19 2 0 20 Nov 2022
Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels Qiuchen Zhang Jing Ma Jian Lou Li Xiong Xiaoqian Jiang NoLa 16 0 0 03 Nov 2022
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach Kaiwen Yang Yanchao Sun Jiahao Su Fengxiang He Xinmei Tian Furong Huang Tianyi Zhou Dacheng Tao 30 13 0 02 Nov 2022
ScoreMix: A Scalable Augmentation Strategy for Training GANs with Limited Data Jie Cao Mandi Luo Junchi Yu Mingmin Yang Ran He 32 4 0 27 Oct 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao W. Wang C. Yuan 21 3 0 11 Oct 2022
Dual Clustering Co-teaching with Consistent Sample Mining for Unsupervised Person Re-Identification Zeqi Chen Zhichao Cui Chi Zhang Jiahuan Zhou Yuehu Liu NoLa 33 17 0 07 Oct 2022
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels Daniel Shwartz Uri Stern D. Weinshall NoLa 33 2 0 02 Oct 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics Shoaib Ahmed Siddiqui Nitarshan Rajkumar Tegan Maharaj David M. Krueger Sara Hooker 37 27 0 20 Sep 2022
Instance-Dependent Noisy Label Learning via Graphical Modelling Arpit Garg Cuong C. Nguyen Rafael Felix Thanh-Toan Do G. Carneiro NoLa 29 27 0 02 Sep 2022
A Study on the Impact of Data Augmentation for Training Convolutional Neural Networks in the Presence of Noisy Labels E. Santana G. Carneiro F. Cordeiro NoLa 24 6 0 23 Aug 2022
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling Boshen Zhang Yuxi Li Yuanpeng Tu Jinlong Peng Yabiao Wang Cunlin Wu Yanghua Xiao Cairong Zhao NoLa 31 6 0 23 Aug 2022
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective Chanwoo Park Sangdoo Yun Sanghyuk Chun AAML 21 32 0 21 Aug 2022
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation Jun Zhuang M. Hasan 25 20 0 21 Aug 2022
Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning D. Hoang Cuong C. Nguyen Cuong Nguyen anh Belagiannis Vasileios G. Carneiro 13 2 0 17 Aug 2022
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels Ganlong Zhao Guanbin Li Yipeng Qin Feng Liu Yizhou Yu NoLa 22 22 0 29 Jul 2022
Unsupervised Learning under Latent Label Shift Manley Roberts P. Mani Saurabh Garg Zachary Chase Lipton OOD 41 9 0 26 Jul 2022
W2N:Switching From Weak Supervision to Noisy Supervision for Object Detection Zitong Huang Yiping Bao Bowen Dong Erjin Zhou W. Zuo WSOD 19 16 0 25 Jul 2022
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer Yingyi Chen Xiaoke Shen Yahui Liu Qinghua Tao Johan A. K. Suykens AAML ViT 23 22 0 25 Jul 2022
Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection Gaoang Wang Yibing Zhan Xinchao Wang Min-Gyoo Song K. Nahrstedt 24 11 0 24 Jul 2022
Learning from Data with Noisy Labels Using Temporal Self-Ensemble Jun Ho Lee J. Baik Taebaek Hwang J. Choi NoLa 25 1 0 21 Jul 2022
Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition Yuhang Zhang Chengrui Wang Xu Ling Weihong Deng 25 136 0 21 Jul 2022
Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation Lars Schmarje Vasco Grossmann Claudius Zelenka S. Dippel R. Kiko ... M. Pastell J. Stracke A. Valros N. Volkmann Reinahrd Koch 40 34 0 13 Jul 2022
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets Yingsong Huang Bing Bai Shengwei Zhao Kun Bai Fei-Yue Wang NoLa 23 43 0 12 Jul 2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State Xinshao Wang Yang Hua Elyor Kodirov S. Mukherjee David A. Clifton N. Robertson 15 6 0 30 Jun 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang Li Shen Jian Yang Chen Gong NoLa 27 5 0 27 Jun 2022