Unsupervised Label Noise Modeling and Loss Correction

25 April 2019

Papers citing "Unsupervised Label Noise Modeling and Loss Correction"

50 / 106 papers shown

Title
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher Jing Jiang Weihong Deng 24 23 0 28 May 2022
ReSmooth: Detecting and Utilizing OOD Samples when Training with Data Augmentation Chenyang Wang Junjun Jiang Xiong Zhou Xianming Liu 30 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
Towards Robust Adaptive Object Detection under Noisy Annotations Xinyu Liu Wuyang Li Qiushi Yang Baopu Li Yixuan Yuan 13 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 20 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
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
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers Deebul Nair Nico Hochgeschwender Miguel A. Olivares-Mendez OOD 22 7 0 03 Feb 2022
Automatic Pharma News Categorization S. Adaszewski P. Kuner Ralf J. Jaeger OOD 16 3 0 28 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
Sample Selection for Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 13 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 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
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
Towards Understanding the Data Dependency of Mixup-style Training Muthuraman Chidambaram Xiang Wang Yuzheng Hu Chenwei Wu Rong Ge UQCV 39 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
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
Learning with Noisy Labels for Robust Point Cloud Segmentation Shuquan Ye Dongdong Chen Songfang Han Jing Liao 3DPC 23 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 11 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 17 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 25 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 19 20 0 07 May 2021
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew S. Lan NoLa 16 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 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 20 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
On the Robustness of Monte Carlo Dropout Trained with Noisy Labels Purvi Goel Li Chen NoLa 28 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 13 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 19 3 0 01 Mar 2021
Typing Errors in Factual Knowledge Graphs: Severity and Possible Ways Out Peiran Yao Denilson Barbosa 29 6 0 03 Feb 2021
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 29 122 0 10 Dec 2020
A Topological Filter for Learning with Label Noise Pengxiang Wu Songzhu Zheng Mayank Goswami Dimitris N. Metaxas Chao Chen NoLa 9 112 0 09 Dec 2020
Multi-Objective Interpolation Training for Robustness to Label Noise Diego Ortego Eric Arazo Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 16 112 0 08 Dec 2020
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 101 34 0 08 Dec 2020
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
When Optimizing $f$ -divergence is Robust with Label Noise Jiaheng Wei Yang Liu 24 54 0 07 Nov 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 19 1,276 0 03 Oct 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 30 429 0 22 Sep 2020
MoPro: Webly Supervised Learning with Momentum Prototypes Junnan Li Caiming Xiong S. Hoi 21 94 0 17 Sep 2020