v1v2v3 (latest)

Combating noisy labels by agreement: A joint training method with co-regularization

5 March 2020

Papers citing "Combating noisy labels by agreement: A joint training method with co-regularization"

50 / 280 papers shown

Title
Noise-Resistant Deep Metric Learning with Probabilistic Instance Filtering Chang-rui Liu Han Yu Boyang Albert Li Zhiqi Shen Zhanning Gao Peiran Ren Xuansong Xie Li-zhen Cui Chunyan Miao NoLa 64 0 0 03 Aug 2021
Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions Anil Rahate Rahee Walambe S. Ramanna K. Kotecha 105 142 0 29 Jul 2021
Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation Shuailin Li Zhitong Gao Xuming He NoLa 71 27 0 21 Jul 2021
Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy Annotations Darshan Gera B. S 69 7 0 10 Jul 2021
Adaptive Sample Selection for Robust Learning under Label Noise Deep Patel P. Sastry OOD NoLa 99 30 0 29 Jun 2021
Bayesian Statistics Guided Label Refurbishment Mechanism: Mitigating Label Noise in Medical Image Classification Mengdi Gao Ximeng Feng Mufeng Geng Zhe Jiang Lei Zhu Xiangxi Meng Chuanqing Zhou Qiushi Ren Yanye Lu BDL NoLa 43 6 0 23 Jun 2021
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise Hongxin Wei Lue Tao Renchunzi Xie Bo An NoLa 73 86 0 21 Jun 2021
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion Xian-Jin Gui Wei Wang Zhang-Hao Tian NoLa 70 48 0 17 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 84 32 0 09 Jun 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels Jiaheng Wei Hangyu Liu Tongliang Liu Gang Niu Masashi Sugiyama Yang Liu NoLa 133 72 0 08 Jun 2021
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels Xiaobo Xia Tongliang Liu Bo Han Biwei Huang Jun Yu Gang Niu Masashi Sugiyama NoLa 77 113 0 01 Jun 2021
Training Classifiers that are Universally Robust to All Label Noise Levels Jingyi Xu Tony Q.S. Quek Kai Fong Ernest Chong NoLa 55 2 0 27 May 2021
Faster Meta Update Strategy for Noise-Robust Deep Learning Youjiang Xu Linchao Zhu Lu Jiang Yi Yang 75 51 0 30 Apr 2021
Boosting Co-teaching with Compression Regularization for Label Noise Yingyi Chen Xin Shen S. Hu Johan A. K. Suykens NoLa 83 47 0 28 Apr 2021
A Framework using Contrastive Learning for Classification with Noisy Labels Madalina Ciortan R. Dupuis Thomas Peel VLM NoLa 47 12 0 19 Apr 2021
Learning from Noisy Labels for Entity-Centric Information Extraction Wenxuan Zhou Muhao Chen NoLa 66 65 0 17 Apr 2021
Joint Negative and Positive Learning for Noisy Labels Youngdong Kim Juseung Yun Hyounguk Shon Junmo Kim NoLa 76 63 0 14 Apr 2021
Divergence Optimization for Noisy Universal Domain Adaptation Qing Yu Atsushi Hashimoto Yoshitaka Ushiku NoLa 62 27 0 01 Apr 2021
Noise-resistant Deep Metric Learning with Ranking-based Instance Selection Chang-rui Liu Han Yu Boyang Albert Li Zhiqi Shen Zhanning Gao Peiran Ren Xuansong Xie Li-zhen Cui Chunyan Miao NoLa 80 38 0 30 Mar 2021
Transform consistency for learning with noisy labels Rumeng Yi Yaping Huang NoLa 44 4 0 25 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 106 135 0 24 Mar 2021
Co-matching: Combating Noisy Labels by Augmentation Anchoring Yangdi Lu Yang Bo Wenbo He NoLa 50 7 0 23 Mar 2021
Detecting Label Noise via Leave-One-Out Cross-Validation Yu-Hang Tang Yuanran Zhu W. A. Jong 48 3 0 21 Mar 2021
Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction Hao-Chiang Shao Hsin-Chieh Wang Weng-Tai Su Chia-Wen Lin NoLa 47 6 0 13 Mar 2021
DST: Data Selection and joint Training for Learning with Noisy Labels Yi Wei Xue Mei Xin Liu Pengxiang Xu NoLa 49 3 0 01 Mar 2021
Searching for Robustness: Loss Learning for Noisy Classification Tasks Boyan Gao Henry Gouk Timothy M. Hospedales OOD NoLa 78 18 0 27 Feb 2021
Multiplicative Reweighting for Robust Neural Network Optimization Noga Bar Tomer Koren Raja Giryes OOD NoLa 81 9 0 24 Feb 2021
Learning Deep Neural Networks under Agnostic Corrupted Supervision Boyang Liu Mengying Sun Ding Wang P. Tan Jiayu Zhou 79 5 0 12 Feb 2021
Understanding Instance-Level Label Noise: Disparate Impacts and Treatments Yang Liu NoLa 55 35 0 10 Feb 2021
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels Zhaowei Zhu Yiwen Song Yang Liu NoLa 99 93 0 10 Feb 2021
Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization Yivan Zhang Gang Niu Masashi Sugiyama NoLa 72 82 0 04 Feb 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise Zhaowei Zhu Tongliang Liu Yang Liu NoLa 90 129 0 22 Dec 2020
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting Hongxin Wei Lei Feng Rongpin Wang Bo An NoLa 73 6 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 81 117 0 08 Dec 2020
A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations? F. Cordeiro G. Carneiro NoLa 110 48 0 05 Dec 2020
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection Tiancai Wang Tong Yang Jiale Cao Xinming Zhang 45 48 0 03 Dec 2020
Robust Federated Learning with Noisy Labels Seunghan Yang Hyoungseob Park Junyoung Byun Changick Kim FedML NoLa 64 80 0 03 Dec 2020
Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels Xiaobo Xia Tongliang Liu Bo Han Nannan Wang Jiankang Deng Jiatong Li Yinian Mao NoLa 71 11 0 02 Dec 2020
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning Zhuowei Wang Jing Jiang Bo Han Lei Feng Bo An Gang Niu Guodong Long NoLa 79 17 0 02 Dec 2020
RNNP: A Robust Few-Shot Learning Approach Pratik Mazumder Pravendra Singh Vinay P. Namboodiri NoLa 35 18 0 22 Nov 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 97 163 0 09 Nov 2020
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach Hao Cheng Zhaowei Zhu Xingyu Li Yifei Gong Xing Sun Yang Liu NoLa 83 209 0 05 Oct 2020
Pointwise Binary Classification with Pairwise Confidence Comparisons Lei Feng Senlin Shu Nan Lu Bo Han Miao Xu Gang Niu Bo An Masashi Sugiyama 97 23 0 05 Oct 2020
Weak-shot Fine-grained Classification via Similarity Transfer Junjie Chen Li Niu Liu Liu Liqing Zhang 98 21 0 19 Sep 2020
Provably Consistent Partial-Label Learning Lei Feng Jiaqi Lv Bo Han Miao Xu Gang Niu Xin Geng Bo An Masashi Sugiyama 68 150 0 17 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 136 1,004 0 16 Jul 2020
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels Songhua Wu Xiaobo Xia Tongliang Liu Bo Han Biwei Huang Nannan Wang Haifeng Liu Gang Niu NoLa 73 53 0 14 Jun 2020
ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks Xinshao Wang Yang Hua Elyor Kodirov David Clifton N. Robertson NoLa 81 61 0 07 May 2020
No Regret Sample Selection with Noisy Labels H. Song N. Mitsuo S. Uchida D. Suehiro NoLa 58 5 0 06 Mar 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 132 108 0 11 Jan 2020