Unsupervised Label Noise Modeling and Loss Correction

25 April 2019

Papers citing "Unsupervised Label Noise Modeling and Loss Correction"

50 / 115 papers shown

Title
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
Eliciting and Learning with Soft Labels from Every Annotator K. M. Collins Umang Bhatt Adrian Weller 19 44 0 02 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 19 6 0 30 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
Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors Jianfei Yang Xiangyu Peng Kaidi Wang Zheng Hua Zhu Jiashi Feng Lihua Xie Yang You 29 27 0 28 May 2022
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher Jing Jiang Weihong Deng 29 23 0 28 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 37 39 0 02 May 2022
Towards Robust Adaptive Object Detection under Noisy Annotations Xinyu Liu Wuyang Li Qiushi Yang Baopu Li Yixuan Yuan 17 29 0 06 Apr 2022
Self-Distillation from the Last Mini-Batch for Consistency Regularization Yiqing Shen Liwu Xu Yuzhe Yang Yaqian Li Yandong Guo 15 60 0 30 Mar 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 98 0 28 Mar 2022
Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li Xiaobo Xia Shiming Ge Tongliang Liu NoLa 24 172 0 08 Mar 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 41 3 0 09 Feb 2022
Learning with Neighbor Consistency for Noisy Labels Ahmet Iscen Jack Valmadre Anurag Arnab Cordelia Schmid NoLa 41 75 0 04 Feb 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers Deebul Nair Nico Hochgeschwender Miguel A. Olivares-Mendez OOD 30 7 0 03 Feb 2022
Automatic Pharma News Categorization S. Adaszewski P. Kuner Ralf J. Jaeger OOD 16 3 0 28 Dec 2021
Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labeling Dat T. Huynh Jason Kuen Zhe-nan Lin Jiuxiang Gu Ehsan Elhamifar ISeg VLM 27 83 0 24 Nov 2021
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise Chen Feng Georgios Tzimiropoulos Ioannis Patras NoLa 24 18 0 22 Nov 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 29 19 0 09 Nov 2021
Sample Selection for Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 21 61 0 27 Oct 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 30 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 26 8 0 20 Oct 2021
Clean or Annotate: How to Spend a Limited Data Collection Budget Derek Chen Zhou Yu Samuel R. Bowman 35 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 40 39 0 14 Oct 2021
Towards Understanding the Data Dependency of Mixup-style Training Muthuraman Chidambaram Xiang Wang Yuzheng Hu Chenwei Wu Rong Ge UQCV 47 24 0 14 Oct 2021
Knowledge Distillation with Noisy Labels for Natural Language Understanding Shivendra Bhardwaj Abbas Ghaddar Ahmad Rashid Khalil Bibi Cheng-huan Li A. Ghodsi Philippe Langlais Mehdi Rezagholizadeh 19 1 0 21 Sep 2021
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training A. Gómez-Ríos Julián Luengo Francisco Herrera OOD NoLa 19 0 0 08 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 76 116 0 05 Aug 2021
Learning with Noisy Labels for Robust Point Cloud Segmentation Shuquan Ye Dongdong Chen Songfang Han Jing Liao 3DPC 31 51 0 29 Jul 2021
Mitigating Memorization in Sample Selection for Learning with Noisy Labels Kyeongbo Kong Junggi Lee Youngchul Kwak Young-Rae Cho Seong-Eun Kim Woo‐Jin Song NoLa 18 0 0 08 Jul 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
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion Xian-Jin Gui Wei Wang Zhang-Hao Tian NoLa 27 44 0 17 Jun 2021
Self-paced Resistance Learning against Overfitting on Noisy Labels Xiaoshuang Shi Zhenhua Guo Fuyong Xing Yun Liang Xiaofeng Zhu NoLa 21 20 0 07 May 2021
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew S. Lan NoLa 21 58 0 19 Apr 2021
Noisy-Labeled NER with Confidence Estimation Kun Liu Yao Fu Chuanqi Tan Mosha Chen Ningyu Zhang Songfang Huang Sheng Gao NoLa 30 60 0 09 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 26 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 28 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 Zhang Zhenmin Tang NoLa 33 133 0 24 Mar 2021
On the Robustness of Monte Carlo Dropout Trained with Noisy Labels Purvi Goel Li Chen NoLa 30 15 0 22 Mar 2021
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment F. Cordeiro Ragav Sachdeva Vasileios Belagiannis Ian Reid G. Carneiro NoLa 11 77 0 06 Mar 2021
Unified Robust Training for Graph NeuralNetworks against Label Noise Yayong Li Jie Yin Ling-Hao Chen NoLa 24 29 0 05 Mar 2021
DST: Data Selection and joint Training for Learning with Noisy Labels Yi Wei Xue Mei Xin Liu Pengxiang Xu NoLa 24 3 0 01 Mar 2021
Typing Errors in Factual Knowledge Graphs: Severity and Possible Ways Out Peiran Yao Denilson Barbosa 31 6 0 03 Feb 2021
Iterative label cleaning for transductive and semi-supervised few-shot learning Michalis Lazarou Tania Stathaki Yannis Avrithis 40 61 0 14 Dec 2020
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 40 122 0 10 Dec 2020