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"

45 / 245 papers shown

Title
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 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 32 69 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 17 110 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 11 2 0 27 May 2021
Faster Meta Update Strategy for Noise-Robust Deep Learning Youjiang Xu Linchao Zhu Lu Jiang Yi Yang 25 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 37 45 0 28 Apr 2021
A Framework using Contrastive Learning for Classification with Noisy Labels Madalina Ciortan R. Dupuis Thomas Peel VLM NoLa 21 12 0 19 Apr 2021
Learning from Noisy Labels for Entity-Centric Information Extraction Wenxuan Zhou Muhao Chen NoLa 12 65 0 17 Apr 2021
Joint Negative and Positive Learning for Noisy Labels Youngdong Kim Juseung Yun Hyounguk Shon Junmo Kim NoLa 20 60 0 14 Apr 2021
Divergence Optimization for Noisy Universal Domain Adaptation Qing Yu Atsushi Hashimoto Yoshitaka Ushiku NoLa 20 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 C. Miao NoLa 25 38 0 30 Mar 2021
Transform consistency for learning with noisy labels Rumeng Yi Yaping Huang NoLa 22 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 33 133 0 24 Mar 2021
Co-matching: Combating Noisy Labels by Augmentation Anchoring Yangdi Lu Yang Bo Wenbo He NoLa 19 7 0 23 Mar 2021
Detecting Label Noise via Leave-One-Out Cross-Validation Yu-Hang Tang Yuanran Zhu W. A. Jong 17 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 14 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 19 3 0 01 Mar 2021
Searching for Robustness: Loss Learning for Noisy Classification Tasks Boyan Gao Henry Gouk Timothy M. Hospedales OOD NoLa 23 18 0 27 Feb 2021
Multiplicative Reweighting for Robust Neural Network Optimization Noga Bar Tomer Koren Raja Giryes OOD NoLa 13 9 0 24 Feb 2021
Learning Deep Neural Networks under Agnostic Corrupted Supervision Boyang Liu Mengying Sun Ding Wang P. Tan Jiayu Zhou 20 5 0 12 Feb 2021
Understanding Instance-Level Label Noise: Disparate Impacts and Treatments Yang Liu NoLa 8 35 0 10 Feb 2021
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels Zhaowei Zhu Yiwen Song Yang Liu NoLa 13 91 0 10 Feb 2021
Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization Yivan Zhang Gang Niu Masashi Sugiyama NoLa 28 78 0 04 Feb 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise Zhaowei Zhu Tongliang Liu Yang Liu NoLa 14 126 0 22 Dec 2020
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting Hongxin Wei Lei Feng R. Wang Bo An NoLa 22 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 21 112 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 45 45 0 05 Dec 2020
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection Tiancai Wang Tong Yang Jiale Cao Xinming Zhang 17 47 0 03 Dec 2020
Robust Federated Learning with Noisy Labels Seunghan Yang Hyoungseob Park Junyoung Byun Changick Kim FedML NoLa 16 76 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 14 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 33 17 0 02 Dec 2020
RNNP: A Robust Few-Shot Learning Approach Pratik Mazumder Pravendra Singh Vinay P. Namboodiri NoLa 13 17 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 24 158 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 22 200 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 33 21 0 05 Oct 2020
Weak-shot Fine-grained Classification via Similarity Transfer Junjie Chen Li Niu Liu Liu Liqing Zhang 28 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 17 141 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 24 958 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 8 53 0 14 Jun 2020
ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks Xinshao Wang Yang Hua Elyor Kodirov David A. Clifton N. Robertson NoLa 24 60 0 07 May 2020
No Regret Sample Selection with Noisy Labels H. Song N. Mitsuo S. Uchida D. Suehiro NoLa 25 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 26 104 0 11 Jan 2020
Learning with Multiple Complementary Labels Lei Feng Takuo Kaneko Bo Han Gang Niu Bo An Masashi Sugiyama 20 92 0 30 Dec 2019
Wasserstein Adversarial Regularization (WAR) on label noise Kilian Fatras B. Bushan Sylvain Lobry Rémi Flamary D. Tuia Nicolas Courty 11 24 0 08 Apr 2019
Classification from Pairwise Similarity and Unlabeled Data Han Bao Gang Niu Masashi Sugiyama 165 87 0 12 Feb 2018