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 / 215 papers shown

Title
Improve Noise Tolerance of Robust Loss via Noise-Awareness Kehui Ding Jun Shu Deyu Meng Zongben Xu NoLa 17 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 23 0 0 04 Jan 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels Yikai Wang Yanwei Fu Xinwei Sun NoLa 36 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 43 2 0 02 Jan 2023
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction Dylan Sam J. Zico Kolter NoLa OffRL 29 13 0 13 Dec 2022
Model and Data Agreement for Learning with Noisy Labels Yuhang Zhang Weihong Deng Xingchen Cui Yunfeng Yin Hongzhi Shi Dongchao Wen NoLa 24 5 0 02 Dec 2022
On Robust Learning from Noisy Labels: A Permutation Layer Approach Salman Alsubaihi Mohammed Alkhrashi Raied Aljadaany Fahad Albalawi Bernard Ghanem NoLa 13 0 0 29 Nov 2022
A Benchmark of Long-tailed Instance Segmentation with Noisy Labels Guanlin Li Guowen Xu Tianwei Zhang NoLa ISeg 16 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 24 19 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 W. Wang NoLa 19 2 0 20 Nov 2022
Robust Training of Graph Neural Networks via Noise Governance Siyi Qian Haochao Ying Renjun Hu Jingbo Zhou Jintai Chen D. Z. Chen Jian Wu NoLa 25 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 16 0 0 03 Nov 2022
The Curious Case of Benign Memorization Sotiris Anagnostidis Gregor Bachmann Lorenzo Noci Thomas Hofmann AAML 32 8 0 25 Oct 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao W. Wang C. Yuan 16 3 0 11 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 33 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 44 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 25 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 35 27 0 20 Sep 2022
Reduction from Complementary-Label Learning to Probability Estimates Weipeng Lin Hsuan-Tien Lin 13 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 23 2 0 16 Sep 2022
Class-Level Logit Perturbation Mengyang Li Fengguang Su O. Wu Tianjin University AAML 29 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 30 1 0 12 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 24 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 29 6 0 23 Aug 2022
ProPaLL: Probabilistic Partial Label Learning Lukasz Struski Jacek Tabor Bartosz Zieliñski 14 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 13 2 0 17 Aug 2022
Unsupervised Learning under Latent Label Shift Manley Roberts P. Mani Saurabh Garg Zachary Chase Lipton OOD 39 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 19 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 19 136 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 23 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 13 6 0 30 Jun 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang Li Shen Jian Yang Chen Gong NoLa 15 5 0 27 Jun 2022
On making optimal transport robust to all outliers Kilian Fatras OT 11 0 0 23 Jun 2022
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation De-Chun Cheng Tongliang Liu Yixiong Ning Nannan Wang Bo Han Gang Niu Xinbo Gao Masashi Sugiyama NoLa 35 65 0 06 Jun 2022
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile Dong Chen Lingfei Wu Siliang Tang Xiao Yun Bo Long Yueting Zhuang VLM NoLa 19 9 0 04 Jun 2022
Task-Adaptive Pre-Training for Boosting Learning With Noisy Labels: A Study on Text Classification for African Languages D. Zhu Michael A. Hedderich Fangzhou Zhai David Ifeoluwa Adelani Dietrich Klakow NoLa 32 0 0 03 Jun 2022
Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space Diane Oyen Michal Kucer N. Hengartner H. Singh NoLa OOD 28 13 0 02 Jun 2022
Context-based Virtual Adversarial Training for Text Classification with Noisy Labels Do-Myoung Lee Yeachan Kim Chang-gyun Seo NoLa 11 2 0 29 May 2022
Bayesian Robust Graph Contrastive Learning Yancheng Wang Yingzhen Yang OOD 23 1 0 27 May 2022
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning Sangmook Kim Wonyoung Shin Soohyuk Jang Hwanjun Song Se-Young Yun 22 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
Is BERT Robust to Label Noise? A Study on Learning with Noisy Labels in Text Classification D. Zhu Michael A. Hedderich Fangzhou Zhai David Ifeoluwa Adelani Dietrich Klakow NoLa 25 32 0 20 Apr 2022
ULF: Unsupervised Labeling Function Correction using Cross-Validation for Weak Supervision Anastasiia Sedova Benjamin Roth 21 0 0 14 Apr 2022
Robust Cross-Modal Representation Learning with Progressive Self-Distillation A. Andonian Shixing Chen Raffay Hamid VLM 19 55 0 10 Apr 2022
Decompositional Generation Process for Instance-Dependent Partial Label Learning Congyu Qiao Ning Xu Xin Geng 112 75 0 08 Apr 2022
Agreement or Disagreement in Noise-tolerant Mutual Learning? Jiarun Liu Daguang Jiang Yukun Yang Ruirui Li NoLa 15 2 0 29 Mar 2022
SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation Xiaoqing Guo Jie Liu Tongliang Liu Yiyuan Yuan 18 27 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
Learning to segment fetal brain tissue from noisy annotations Davood Karimi C. Rollins C. Velasco-Annis Abdelhakim Ouaalam Ali Gholipour 18 25 0 25 Mar 2022