DivideMix: Learning with Noisy Labels as Semi-supervised Learning

18 February 2020

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

50 / 167 papers shown

Title
MSR: Making Self-supervised learning Robust to Aggressive Augmentations Ying-Long Bai Erkun Yang Zhaoqing Wang Yuxuan Du Bo Han Cheng Deng Dadong Wang Tongliang Liu SSL 23 3 0 04 Jun 2022
Hyperspherical Consistency Regularization Cheng Tan Zhangyang Gao Lirong Wu Siyuan Li Stan Z. Li 30 24 0 02 Jun 2022
Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors Jianfei Yang Xiangyu Peng K. Wang Zheng Hua Zhu Jiashi Feng Lihua Xie Yang You 24 27 0 28 May 2022
Bayesian Robust Graph Contrastive Learning Yancheng Wang Yingzhen Yang OOD 23 1 0 27 May 2022
Censor-aware Semi-supervised Learning for Survival Time Prediction from Medical Images Renato Hermoza Gabriel Maicas Jacinto C. Nascimento G. Carneiro 20 6 0 26 May 2022
ReSmooth: Detecting and Utilizing OOD Samples when Training with Data Augmentation Chenyang Wang Junjun Jiang Xiong Zhou Xianming Liu 32 3 0 25 May 2022
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning Sangmook Kim Wonyoung Shin Soohyuk Jang Hwanjun Song Se-Young Yun 29 2 0 03 May 2022
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels Yangdi Lu Wenbo He NoLa 25 39 0 02 May 2022
Agreement or Disagreement in Noise-tolerant Mutual Learning? Jiarun Liu Daguang Jiang Yukun Yang Ruirui Li NoLa 23 2 0 29 Mar 2022
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning Nazmul Karim Mamshad Nayeem Rizve Nazanin Rahnavard Ajmal Saeed Mian M. Shah NoLa 30 97 0 28 Mar 2022
Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li Xiaobo Xia Shiming Ge Tongliang Liu NoLa 19 172 0 08 Mar 2022
Synergistic Network Learning and Label Correction for Noise-robust Image Classification Chen Gong K. Bin E. Seibel Xin Wang Youbing Yin Qi Song NoLa 20 2 0 27 Feb 2022
Dropout can Simulate Exponential Number of Models for Sample Selection Techniques RD Samsung 29 0 0 26 Feb 2022
Debiased Self-Training for Semi-Supervised Learning Baixu Chen Junguang Jiang Ximei Wang Pengfei Wan Jianmin Wang Mingsheng Long 29 85 0 15 Feb 2022
L2B: Learning to Bootstrap Robust Models for Combating Label Noise Yuyin Zhou Xianhang Li Fengze Liu Qingyue Wei Xuxi Chen Lequan Yu Cihang Xie M. Lungren Lei Xing NoLa 39 3 0 09 Feb 2022
Learning with Neighbor Consistency for Noisy Labels Ahmet Iscen Jack Valmadre Anurag Arnab Cordelia Schmid NoLa 28 75 0 04 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 41 3 0 30 Jan 2022
GMM Discriminant Analysis with Noisy Label for Each Class Jian-wei Liu Zheng-ping Ren Run-kun Lu Xiong-lin Luo 27 6 0 25 Jan 2022
PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning Haobo Wang Rui Xiao Yixuan Li Lei Feng Gang Niu Gang Chen J. Zhao VLM 41 25 0 22 Jan 2022
Hard Sample Aware Noise Robust Learning for Histopathology Image Classification Chuang Zhu Wenkai Chen T. Peng Ying Wang M. Jin NoLa 26 71 0 05 Dec 2021
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise Chen Feng Georgios Tzimiropoulos Ioannis Patras NoLa 19 18 0 22 Nov 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 25 19 0 09 Nov 2021
Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation Jeongeun Park Seungyoung Shin Sangheum Hwang Sungjoon Choi 15 5 0 02 Nov 2021
Addressing out-of-distribution label noise in webly-labelled data Paul Albert Diego Ortego Eric Arazo Noel E. O'Connor Kevin McGuinness NoLa 16 16 0 26 Oct 2021
PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels F. Cordeiro Vasileios Belagiannis Ian Reid G. Carneiro NoLa 22 18 0 22 Oct 2021
One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer Yongquan Yang Fengling Li Yani Wei Jie Chen Ning Chen Mohammad H. Alobaidi Hong Bu 18 8 0 20 Oct 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
Clean or Annotate: How to Spend a Limited Data Collection Budget Derek Chen Zhou Yu Samuel R. Bowman 27 13 0 15 Oct 2021
Continual Learning on Noisy Data Streams via Self-Purified Replay C. Kim Jinseo Jeong Sang-chul Moon Gunhee Kim CLL 32 39 0 14 Oct 2021
Fuzzy Overclustering: Semi-Supervised Classification of Fuzzy Labels with Overclustering and Inverse Cross-Entropy Lars Schmarje Johannes Brunger M. Santarossa Simon-Martin Schroder R. Kiko Reinhard Koch 39 17 0 13 Oct 2021
Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning Xinghua Zhang Yu Bowen Tingwen Liu Zhenyu Zhang Jiawei Sheng Mengge Xue Hongbo Xu 16 21 0 09 Oct 2021
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations Sheng Liu Kangning Liu Weicheng Zhu Yiqiu Shen C. Fernandez‐Granda NoLa 26 104 0 07 Oct 2021
Hybrid Dynamic Contrast and Probability Distillation for Unsupervised Person Re-Id De-Chun Cheng Jingyu Zhou N. Wang Xinbo Gao 19 58 0 29 Sep 2021
Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction Jiarun Liu Ruirui Li Chuan Sun OOD NoLa VLM 22 32 0 11 Sep 2021
NGC: A Unified Framework for Learning with Open-World Noisy Data Zhi-Fan Wu Tong Wei Jianwen Jiang Chaojie Mao Mingqian Tang Yu-Feng Li 11 80 0 25 Aug 2021
Co-learning: Learning from Noisy Labels with Self-supervision Cheng Tan Jun-Xiong Xia Lirong Wu Stan Z. Li NoLa 68 116 0 05 Aug 2021
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation Junnan Li Ramprasaath R. Selvaraju Akhilesh Deepak Gotmare Shafiq R. Joty Caiming Xiong S. Hoi FaML 53 1,884 0 16 Jul 2021
A data-centric approach for improving ambiguous labels with combined semi-supervised classification and clustering Lars Schmarje M. Santarossa Simon-Martin Schroder Claudius Zelenka R. Kiko J. Stracke N. Volkmann Reinhard Koch 30 10 0 30 Jun 2021
Adaptive Sample Selection for Robust Learning under Label Noise Deep Patel P. Sastry OOD NoLa 28 29 0 29 Jun 2021
SENT: Sentence-level Distant Relation Extraction via Negative Training Ruotian Ma Tao Gui Linyang Li Qi Zhang Yaqian Zhou Xuanjing Huang 22 28 0 22 Jun 2021
Survey: Image Mixing and Deleting for Data Augmentation Humza Naveed Saeed Anwar Munawar Hayat Kashif Javed Ajmal Mian 30 78 0 13 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 25 114 0 08 Jun 2021
CCMN: A General Framework for Learning with Class-Conditional Multi-Label Noise Ming-Kun Xie Sheng-Jun Huang NoLa 18 25 0 16 May 2021
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels Erik Englesson Hossein Azizpour NoLa 26 103 0 10 May 2021
Self-paced Resistance Learning against Overfitting on Noisy Labels Xiaoshuang Shi Zhenhua Guo Fuyong Xing Yun Liang Xiaofeng Zhu NoLa 19 20 0 07 May 2021
Boosting Co-teaching with Compression Regularization for Label Noise Yingyi Chen Xin Shen S. Hu Johan A. K. Suykens NoLa 37 45 0 28 Apr 2021
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew S. Lan NoLa 19 58 0 19 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 24 6 0 01 Apr 2021
Learning from Pixel-Level Label Noise: A New Perspective for Semi-Supervised Semantic Segmentation Rumeng Yi Yaping Huang Q. Guan Mengyang Pu Runsheng Zhang NoLa 22 27 0 26 Mar 2021
Jo-SRC: A Contrastive Approach for Combating Noisy Labels Yazhou Yao Zeren Sun Chuanyi Zhang Fumin Shen Qi Wu Jian Andrew Zhang Zhenmin Tang NoLa 33 133 0 24 Mar 2021