Instance-specific Label Distribution Regularization for Learning with Label Noise

16 December 2022

Papers citing "Instance-specific Label Distribution Regularization for Learning with Label Noise"

22 / 22 papers shown

Title
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets Yingsong Huang Bing Bai Shengwei Zhao Kun Bai Fei Wang NoLa 68 44 0 12 Jul 2022
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation De Cheng Tongliang Liu Yixiong Ning Nannan Wang Bo Han Gang Niu Xinbo Gao Masashi Sugiyama NoLa 72 65 0 06 Jun 2022
Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels Yikai Wang Xinwei Sun Yanwei Fu NoLa 72 24 0 15 Mar 2022
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations Jiaheng Wei Zhaowei Zhu Weiran Wang Tongliang Liu Gang Niu Yang Liu NoLa 125 253 0 22 Oct 2021
Asymmetric Loss Functions for Learning with Noisy Labels Xiong Zhou Xianming Liu Junjun Jiang Xin Gao Xiangyang Ji NoLa 63 69 0 06 Jun 2021
A Survey on Deep Semi-supervised Learning Xiangli Yang Zixing Song Irwin King Zenglin Xu 108 583 0 28 Feb 2021
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach Hao Cheng Zhaowei Zhu Xingyu Li Yifei Gong Xing Sun Yang Liu NoLa 68 207 0 05 Oct 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 104 566 0 30 Jun 2020
Normalized Loss Functions for Deep Learning with Noisy Labels Xingjun Ma Hanxun Huang Yisen Wang Simone Romano S. Erfani James Bailey NoLa 73 444 0 24 Jun 2020
Are we done with ImageNet? Lucas Beyer Olivier J. Hénaff Alexander Kolesnikov Xiaohua Zhai Aaron van den Oord VLM 121 401 0 12 Jun 2020
Semi-supervised Medical Image Classification with Relation-driven Self-ensembling Model Quande Liu Lequan Yu Luyang Luo Qi Dou Pheng Ann Heng 87 226 0 15 May 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 105 1,030 0 18 Feb 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 98 108 0 11 Jan 2020
SELF: Learning to Filter Noisy Labels with Self-Ensembling Philipp Kratzer Marc Toussaint Thi Phuong Nhung Ngo T. Nguyen Jim Mainprice Thomas Brox NoLa 85 316 0 04 Oct 2019
NLNL: Negative Learning for Noisy Labels Youngdong Kim Junho Yim Juseung Yun Junmo Kim NoLa 49 276 0 19 Aug 2019
Symmetric Cross Entropy for Robust Learning with Noisy Labels Yisen Wang Xingjun Ma Zaiyi Chen Yuan Luo Jinfeng Yi James Bailey NoLa 88 900 0 16 Aug 2019
Are Anchor Points Really Indispensable in Label-Noise Learning? Xiaobo Xia Tongliang Liu N. Wang Bo Han Chen Gong Gang Niu Masashi Sugiyama NoLa 73 379 0 01 Jun 2019
Combating Label Noise in Deep Learning Using Abstention S. Thulasidasan Tanmoy Bhattacharya J. Bilmes Gopinath Chennupati J. Mohd-Yusof NoLa 57 179 0 27 May 2019
Curriculum Loss: Robust Learning and Generalization against Label Corruption Yueming Lyu Ivor W. Tsang NoLa 101 172 0 24 May 2019
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 98 1,453 0 14 Dec 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 339 4,629 0 10 Nov 2016
Temporal Ensembling for Semi-Supervised Learning S. Laine Timo Aila UQCV 185 2,560 0 07 Oct 2016