Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise

14 February 2018

Papers citing "Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise"

50 / 285 papers shown

Title
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State Xinshao Wang Yang Hua Elyor Kodirov S. Mukherjee David A. Clifton N. Robertson 30 6 0 30 Jun 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 39 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 31 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 34 0 0 03 Jun 2022
Deep Learning with Label Noise: A Hierarchical Approach Li-Wei Chen Ningyuan Huang Cong Mu Hayden S. Helm Kate Lytvynets Weiwei Yang Carey E. Priebe NoLa 19 1 0 28 May 2022
Detecting Label Errors by using Pre-Trained Language Models Derek Chong Jenny Hong Christopher D. Manning NoLa 55 21 0 25 May 2022
Distributed Multi-Agent Deep Reinforcement Learning for Robust Coordination against Noise Yoshinari Motokawa T. Sugawara 27 2 0 19 May 2022
Noise-Tolerant Learning for Audio-Visual Action Recognition Haocheng Han Qinghua Zheng Minnan Luo Kaiyao Miao Feng Tian Yuanchun Chen NoLa 35 7 0 16 May 2022
Meta Self-Refinement for Robust Learning with Weak Supervision D. Zhu Xiaoyu Shen Michael A. Hedderich Dietrich Klakow NoLa 32 7 0 15 May 2022
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training Cheng Xue Lequan Yu Pengfei Chen Qi Dou Pheng-Ann Heng NoLa 22 52 0 10 May 2022
CNLL: A Semi-supervised Approach For Continual Noisy Label Learning Nazmul Karim Umar Khalid Ashkan Esmaeili Nazanin Rahnavard NoLa CLL 35 15 0 21 Apr 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 35 32 0 20 Apr 2022
SETTI: A Self-supervised Adversarial Malware Detection Architecture in an IoT Environment Marjan Golmaryami R. Taheri Zahra Pooranian Mohammad Shojafar Pei Xiao 33 12 0 16 Apr 2022
Agreement or Disagreement in Noise-tolerant Mutual Learning? Jiarun Liu Daguang Jiang Yukun Yang Ruirui Li NoLa 23 2 0 29 Mar 2022
Part-based Pseudo Label Refinement for Unsupervised Person Re-identification Y. Cho Woo Jae Kim Seunghoon Hong Sung-eui Yoon 31 166 0 28 Mar 2022
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning Nazmul Karim Mamshad Nayeem Rizve Nazanin Rahnavard Ajmal Mian M. Shah NoLa 37 98 0 28 Mar 2022
Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li Xiaobo Xia Shiming Ge Tongliang Liu NoLa 27 172 0 08 Mar 2022
Robust Training under Label Noise by Over-parameterization Sheng Liu Zhihui Zhu Qing Qu Chong You NoLa OOD 32 106 0 28 Feb 2022
Dropout can Simulate Exponential Number of Models for Sample Selection Techniques RD Samsung 31 0 0 26 Feb 2022
ASSIST: Towards Label Noise-Robust Dialogue State Tracking Fanghua Ye Yue Feng Emine Yilmaz 21 21 0 26 Feb 2022
"Is not the truth the truth?": Analyzing the Impact of User Validations for Bus In/Out Detection in Smartphone-based Surveys Valentino Servizi D. R. Persson Francisco Câmara Pereira Hannah Villadsen Per Bækgaard Inon Peled Otto Anker Nielsen 14 2 0 24 Feb 2022
Tripartite: Tackle Noisy Labels by a More Precise Partition Xuefeng Liang Longshan Yao Xingyu Liu Ying Zhou NoLa 26 9 0 19 Feb 2022
CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep Learning Jun Shu Xiang Yuan Deyu Meng Zongben Xu NoLa 27 33 0 11 Feb 2022
L2B: Learning to Bootstrap Robust Models for Combating Label Noise Yuyin Zhou Xianhang Li Fengze Liu Qingyue Wei Xuxi Chen Lequan Yu Cihang Xie M. Lungren Lei Xing NoLa 47 3 0 09 Feb 2022
Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data Shenwang Jiang Jianan Li Ying Wang Bo Huang Zhang Zhang Tingfa Xu NoLa 34 31 0 30 Dec 2021
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity Dixian Zhu Yiming Ying Tianbao Yang 35 9 0 30 Dec 2021
Semantic Clustering based Deduction Learning for Image Recognition and Classification Wenchi Ma Xuemin Tu Bo Luo Guanghui Wang 36 29 0 25 Dec 2021
Robust Neural Network Classification via Double Regularization Olof Zetterqvist Rebecka Jörnsten J. Jonasson 11 1 0 15 Dec 2021
Hard Sample Aware Noise Robust Learning for Histopathology Image Classification Chuang Zhu Wenkai Chen T. Peng Ying Wang M. Jin NoLa 34 72 0 05 Dec 2021
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection Seong Min Kye Kwanghee Choi Joonyoung Yi Buru Chang NoLa 35 15 0 29 Nov 2021
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise Chen Feng Georgios Tzimiropoulos Ioannis Patras NoLa 27 18 0 22 Nov 2021
CLIP2TV: Align, Match and Distill for Video-Text Retrieval Zijian Gao Qingbin Liu Weiqi Sun S. Chen Dedan Chang Lili Zhao VLM CLIP 31 17 0 10 Nov 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 32 19 0 09 Nov 2021
Learning to Rectify for Robust Learning with Noisy Labels Haoliang Sun Chenhui Guo Qinglai Wei Zhongyi Han Yilong Yin NoLa 106 34 0 08 Nov 2021
Generalized Data Weighting via Class-level Gradient Manipulation Can Chen Shuhao Zheng Xi Chen Erqun Dong Xue Liu Hao Liu Dejing Dou 35 24 0 29 Oct 2021
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 49 242 0 22 Oct 2021
A Fine-Grained Analysis on Distribution Shift Olivia Wiles Sven Gowal Florian Stimberg Sylvestre-Alvise Rebuffi Ira Ktena Krishnamurthy Dvijotham A. Cemgil OOD 236 208 0 21 Oct 2021
Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction Takuma Yagi Md. Tasnimul Hasan Yoichi Sato 22 5 0 19 Oct 2021
Continual Learning on Noisy Data Streams via Self-Purified Replay C. Kim Jinseo Jeong Sang-chul Moon Gunhee Kim CLL 42 39 0 14 Oct 2021
An Empirical Investigation of Learning from Biased Toxicity Labels Neel Nanda J. Uesato Sven Gowal 23 0 0 04 Oct 2021
Robust Temporal Ensembling for Learning with Noisy Labels Abel Brown Benedikt Schifferer R. DiPietro NoLa OOD 14 0 0 29 Sep 2021
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation Kaize Ding Dingcheng Li Alexander Hanbo Li Xing Fan Chenlei Guo Yang Liu Huan Liu 42 6 0 25 Sep 2021
MetaXT: Meta Cross-Task Transfer between Disparate Label Spaces Srinagesh Sharma Guoqing Zheng Ahmed Hassan Awadallah 27 1 0 09 Sep 2021
WALNUT: A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding Guoqing Zheng Giannis Karamanolakis Kai Shu Ahmed Hassan Awadallah SSL 21 1 0 28 Aug 2021
Contrastive Representations for Label Noise Require Fine-Tuning Pierre Nodet V. Lemaire A. Bondu Antoine Cornuéjols 23 1 0 20 Aug 2021
Confidence Adaptive Regularization for Deep Learning with Noisy Labels Yangdi Lu Yang Bo Wenbo He NoLa 30 10 0 18 Aug 2021
Co-learning: Learning from Noisy Labels with Self-supervision Cheng Tan Jun Xia Lirong Wu Stan Z. Li NoLa 76 116 0 05 Aug 2021
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators Cosmin Octavian Pene Amirmasoud Ghiassi Taraneh Younesian Robert Birke Lydia Y. Chen 34 3 0 04 Aug 2021
Learning with Noisy Labels for Robust Point Cloud Segmentation Shuquan Ye Dongdong Chen Songfang Han Jing Liao 3DPC 31 51 0 29 Jul 2021
An Instance-Dependent Simulation Framework for Learning with Label Noise Keren Gu Xander Masotto Vandana Bachani Balaji Lakshminarayanan Jack Nikodem Dong Yin NoLa 21 24 0 23 Jul 2021