Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

13 September 2016

Papers citing "Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach"

50 / 265 papers shown

Title
Complementary to Multiple Labels: A Correlation-Aware Correction Approach Yi Gao Miao Xu Min-Ling Zhang 19 0 0 25 Feb 2023
Practical Knowledge Distillation: Using DNNs to Beat DNNs Chungman Lee Pavlos Anastasios Apostolopulos Igor L. Markov FedML 22 1 0 23 Feb 2023
Latent Class-Conditional Noise Model Jiangchao Yao Bo Han Zhihan Zhou Ya-Qin Zhang Ivor W. Tsang NoLa BDL 33 8 0 19 Feb 2023
Smoothly Giving up: Robustness for Simple Models Tyler Sypherd Nathan Stromberg Richard Nock Visar Berisha Lalitha Sankar 21 1 0 17 Feb 2023
Learning from Noisy Labels with Decoupled Meta Label Purifier Yuanpeng Tu Boshen Zhang Yuxi Li Liang Liu Jian Li Yabiao Wang Chengjie Wang C. Zhao NoLa 49 27 0 14 Feb 2023
Learning from Noisy Crowd Labels with Logics Zhijun Chen Hailong Sun Haoqian He Pengpeng Chen NoLa NAI 32 7 0 13 Feb 2023
When Source-Free Domain Adaptation Meets Learning with Noisy Labels L. Yi Gezheng Xu Pengcheng Xu Jiaqi Li Ruizhi Pu Charles Ling A. McLeod Boyu Wang 23 39 0 31 Jan 2023
Improve Noise Tolerance of Robust Loss via Noise-Awareness Kehui Ding Jun Shu Deyu Meng Zongben Xu NoLa 33 5 0 18 Jan 2023
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach Cuong C. Nguyen Thanh-Toan Do G. Carneiro NoLa 40 0 0 04 Jan 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels Yikai Wang Yanwei Fu Xinwei Sun NoLa 55 8 0 02 Jan 2023
Learning Confident Classifiers in the Presence of Label Noise Asma Ahmed Hashmi Aigerim Zhumabayeva Nikita Kotelevskii A. Agafonov Mohammad Yaqub Maxim Panov Martin Takávc NoLa 61 2 0 02 Jan 2023
Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features Qingrui Jia Xuhong Li Lei Yu Jiang Bian Penghao Zhao Shupeng Li Haoyi Xiong Dejing Dou NoLa 35 5 0 19 Dec 2022
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction Dylan Sam J. Zico Kolter NoLa OffRL 37 13 0 13 Dec 2022
Sources of Noise in Dialogue and How to Deal with Them Derek Chen Zhou Yu 15 2 0 06 Dec 2022
Model and Data Agreement for Learning with Noisy Labels Yuhang Zhang Weihong Deng Xingchen Cui Yunfeng Yin Hongzhi Shi Dongchao Wen NoLa 34 5 0 02 Dec 2022
On Robust Learning from Noisy Labels: A Permutation Layer Approach Salman Alsubaihi Mohammed Alkhrashi Raied Aljadaany Fahad Albalawi Guohao Li NoLa 23 0 0 29 Nov 2022
Establishment of Neural Networks Robust to Label Noise Pengwei Yang Angel Teng Jack Mangos NoLa 16 0 0 28 Nov 2022
A Benchmark of Long-tailed Instance Segmentation with Noisy Labels Guanlin Li Guowen Xu Tianwei Zhang NoLa ISeg 21 0 0 24 Nov 2022
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method Manyi Zhang Xuyang Zhao Jun Yao Chun Yuan Weiran Huang 38 20 0 20 Nov 2022
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels Daehwan Kim Kwang-seok Ryoo Hansang Cho Seung Wook Kim NoLa 24 3 0 20 Nov 2022
Learning from Long-Tailed Noisy Data with Sample Selection and Balanced Loss Lefan Zhang Zhang-Hao Tian Wujun Zhou Wei Wang NoLa 24 2 0 20 Nov 2022
Robust Training of Graph Neural Networks via Noise Governance Siyi Qian Haochao Ying Renjun Hu Jingbo Zhou Jintai Chen Danny Chen Jian Wu NoLa 33 34 0 12 Nov 2022
Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels Qiuchen Zhang Jing Ma Jian Lou Li Xiong Xiaoqian Jiang NoLa 21 0 0 03 Nov 2022
The Curious Case of Benign Memorization Sotiris Anagnostidis Gregor Bachmann Lorenzo Noci Thomas Hofmann AAML 49 8 0 25 Oct 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 21 3 0 11 Oct 2022
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition Kiyoon Kim Davide Moltisanti Oisin Mac Aodha Laura Sevilla-Lara 16 0 0 10 Oct 2022
Dual Clustering Co-teaching with Consistent Sample Mining for Unsupervised Person Re-Identification Zeqi Chen Zhichao Cui Chi Zhang Jiahuan Zhou Yuehu Liu NoLa 46 17 0 07 Oct 2022
FedMT: Federated Learning with Mixed-type Labels Qiong Zhang Jing Peng Xin Zhang A. Talhouk Gang Niu Xiaoxiao Li FedML 54 0 0 05 Oct 2022
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels Daniel Shwartz Uri Stern D. Weinshall NoLa 33 2 0 02 Oct 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics Shoaib Ahmed Siddiqui Nitarshan Rajkumar Tegan Maharaj David M. Krueger Sara Hooker 42 27 0 20 Sep 2022
Reduction from Complementary-Label Learning to Probability Estimates Weipeng Lin Hsuan-Tien Lin 33 9 0 20 Sep 2022
Weakly Supervised Medical Image Segmentation With Soft Labels and Noise Robust Loss B. Felfeliyan A. Hareendranathan G. Kuntze S. Wichuk Nils D. Forkert Jacob L. Jaremko J. Ronsky NoLa 35 2 0 16 Sep 2022
Robust Product Classification with Instance-Dependent Noise Huy-Thanh Nguyen Devashish Khatwani NoLa 34 8 0 14 Sep 2022
Class-Level Logit Perturbation Mengyang Li Fengguang Su O. Wu Tianjin University AAML 31 3 0 13 Sep 2022
Bayesian Learning for Disparity Map Refinement for Semi-Dense Active Stereo Vision Laurent Valentin Jospin Hamid Laga F. Boussaïd Bennamoun 32 1 0 12 Sep 2022
Instance-Dependent Noisy Label Learning via Graphical Modelling Arpit Garg Cuong C. Nguyen Rafael Felix Thanh-Toan Do G. Carneiro NoLa 34 27 0 02 Sep 2022
A Study on the Impact of Data Augmentation for Training Convolutional Neural Networks in the Presence of Noisy Labels E. Santana G. Carneiro F. Cordeiro NoLa 29 6 0 23 Aug 2022
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling Boshen Zhang Yuxi Li Yuanpeng Tu Jinlong Peng Yabiao Wang Cunlin Wu Yanghua Xiao Cairong Zhao NoLa 38 6 0 23 Aug 2022
ProPaLL: Probabilistic Partial Label Learning Lukasz Struski Jacek Tabor Bartosz Zieliñski 28 2 0 21 Aug 2022
Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning D. Hoang Cuong C. Nguyen Cuong Nguyen anh Belagiannis Vasileios G. Carneiro 25 2 0 17 Aug 2022
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels Ganlong Zhao Guanbin Li Yipeng Qin Feng Liu Yizhou Yu NoLa 33 22 0 29 Jul 2022
Unsupervised Learning under Latent Label Shift Manley Roberts P. Mani Saurabh Garg Zachary Chase Lipton OOD 57 9 0 26 Jul 2022
Learning from Data with Noisy Labels Using Temporal Self-Ensemble Jun Ho Lee J. Baik Taebaek Hwang J. Choi NoLa 28 1 0 21 Jul 2022
Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition Yuhang Zhang Chengrui Wang Xu Ling Weihong Deng 35 136 0 21 Jul 2022
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
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
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang Li Shen Jian Yang Chen Gong NoLa 27 5 0 27 Jun 2022
On making optimal transport robust to all outliers Kilian Fatras OT 19 0 0 23 Jun 2022
Transductive CLIP with Class-Conditional Contrastive Learning Junchu Huang Weijie Chen Shicai Yang Di Xie Shiliang Pu Yueting Zhuang VLM BDL NoLa 16 6 0 13 Jun 2022
Certifying Data-Bias Robustness in Linear Regression Anna P. Meyer Aws Albarghouthi Loris Dántoni 29 3 0 07 Jun 2022