Training Deep Neural Networks on Noisy Labels with Bootstrapping

20 December 2014

Papers citing "Training Deep Neural Networks on Noisy Labels with Bootstrapping"

50 / 166 papers shown

Title
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
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher Jing Jiang Weihong Deng 24 23 0 28 May 2022
Wireless Deep Video Semantic Transmission Sixian Wang Jincheng Dai Zijian Liang K. Niu Zhongwei Si Chao Dong Xiaoqi Qin Ping Zhang 3DV DiffM 46 141 0 26 May 2022
Detecting Label Errors by using Pre-Trained Language Models Derek Chong Jenny Hong Christopher D. Manning NoLa 38 21 0 25 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
Robust Cross-Modal Representation Learning with Progressive Self-Distillation A. Andonian Shixing Chen Raffay Hamid VLM 21 55 0 10 Apr 2022
Towards Robust Adaptive Object Detection under Noisy Annotations Xinyu Liu Wuyang Li Qiushi Yang Baopu Li Yixuan Yuan 13 29 0 06 Apr 2022
Self-Distillation from the Last Mini-Batch for Consistency Regularization Yiqing Shen Liwu Xu Yuzhe Yang Yaqian Li Yandong Guo 15 60 0 30 Mar 2022
Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation Yongliang Ding Tao Zhou Chuang Zhang Yijing Luo Juan Tang Chen Gong NoLa 22 4 0 21 Mar 2022
Synergistic Network Learning and Label Correction for Noise-robust Image Classification Chen Gong K. Bin E. Seibel Xin Wang Youbing Yin Qi Song NoLa 17 2 0 27 Feb 2022
A Semi-supervised Learning Approach with Two Teachers to Improve Breakdown Identification in Dialogues Qian Lin Hwee Tou Ng 22 4 0 22 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 39 3 0 09 Feb 2022
Learning with Neighbor Consistency for Noisy Labels Ahmet Iscen Jack Valmadre Anurag Arnab Cordelia Schmid NoLa 28 75 0 04 Feb 2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise? Yexiong Lin Yu Yao Yuxuan Du Jun Yu Bo Han Mingming Gong Tongliang Liu NoLa 41 3 0 30 Jan 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis Shuai Zhang M. Wang Sijia Liu Pin-Yu Chen Jinjun Xiong SSL MLT 39 22 0 21 Jan 2022
Automatic Pharma News Categorization S. Adaszewski P. Kuner Ralf J. Jaeger OOD 16 3 0 28 Dec 2021
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation Yi Li Yiqun Duan Zhanghui Kuang Yimin Chen Wayne Zhang Xiaomeng Li 22 72 0 14 Dec 2021
Hard Sample Aware Noise Robust Learning for Histopathology Image Classification Chuang Zhu Wenkai Chen T. Peng Ying Wang M. Jin NoLa 26 71 0 05 Dec 2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise Abhishek Kumar Ehsan Amid NoLa 25 19 0 09 Nov 2021
Addressing out-of-distribution label noise in webly-labelled data Paul Albert Diego Ortego Eric Arazo Noel E. O'Connor Kevin McGuinness NoLa 16 16 0 26 Oct 2021
One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer Yongquan Yang Fengling Li Yani Wei Jie Chen Ning Chen Mohammad H. Alobaidi Hong Bu 18 8 0 20 Oct 2021
Clean or Annotate: How to Spend a Limited Data Collection Budget Derek Chen Zhou Yu Samuel R. Bowman 27 13 0 15 Oct 2021
Continual Learning on Noisy Data Streams via Self-Purified Replay C. Kim Jinseo Jeong Sang-chul Moon Gunhee Kim CLL 32 39 0 14 Oct 2021
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations Sheng Liu Kangning Liu Weicheng Zhu Yiqiu Shen C. Fernandez‐Granda NoLa 26 104 0 07 Oct 2021
Assessing the Quality of the Datasets by Identifying Mislabeled Samples Vaibhav Pulastya Gaurav Nuti Yash Kumar Atri Tanmoy Chakraborty NoLa 25 5 0 10 Sep 2021
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training A. Gómez-Ríos Julián Luengo Francisco Herrera OOD NoLa 19 0 0 08 Sep 2021
Co-learning: Learning from Noisy Labels with Self-supervision Cheng Tan Jun-Xiong Xia Lirong Wu Stan Z. Li NoLa 68 116 0 05 Aug 2021
Learning with Noisy Labels for Robust Point Cloud Segmentation Shuquan Ye Dongdong Chen Songfang Han Jing Liao 3DPC 23 51 0 29 Jul 2021
Mitigating Memorization in Sample Selection for Learning with Noisy Labels Kyeongbo Kong Junggi Lee Youngchul Kwak Young-Rae Cho Seong-Eun Kim Woo‐Jin Song NoLa 11 0 0 08 Jul 2021
Adaptive Sample Selection for Robust Learning under Label Noise Deep Patel P. Sastry OOD NoLa 28 29 0 29 Jun 2021
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs Enyan Dai Charu C. Aggarwal Suhang Wang NoLa 25 114 0 08 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
Correlated Input-Dependent Label Noise in Large-Scale Image Classification Mark Collier Basil Mustafa Efi Kokiopoulou Rodolphe Jenatton Jesse Berent NoLa 176 53 0 19 May 2021
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels Erik Englesson Hossein Azizpour NoLa 26 103 0 10 May 2021
Self-paced Resistance Learning against Overfitting on Noisy Labels Xiaoshuang Shi Zhenhua Guo Fuyong Xing Yun Liang Xiaofeng Zhu NoLa 19 20 0 07 May 2021
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew S. Lan NoLa 19 58 0 19 Apr 2021
Collaborative Label Correction via Entropy Thresholding Hao Wu Jiangchao Yao Jiajie Wang Yinru Chen Ya-Qin Zhang Yanfeng Wang NoLa 14 4 0 31 Mar 2021
Jo-SRC: A Contrastive Approach for Combating Noisy Labels Yazhou Yao Zeren Sun Chuanyi Zhang Fumin Shen Qi Wu Jian Andrew Zhang Zhenmin Tang NoLa 33 133 0 24 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
On the Reproducibility of Neural Network Predictions Srinadh Bhojanapalli Kimberly Wilber Andreas Veit A. S. Rawat Seungyeon Kim A. Menon Sanjiv Kumar 21 35 0 05 Feb 2021
Analysing the Noise Model Error for Realistic Noisy Label Data Michael A. Hedderich D. Zhu Dietrich Klakow NoLa 21 19 0 24 Jan 2021
Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification Yongxing Dai Jun Liu Yan Bai Zekun Tong Ling-yu Duan 16 77 0 26 Dec 2020
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 29 122 0 10 Dec 2020
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting Hongxin Wei Lei Feng R. Wang Bo An NoLa 17 6 0 09 Dec 2020
A Topological Filter for Learning with Label Noise Pengxiang Wu Songzhu Zheng Mayank Goswami Dimitris N. Metaxas Chao Chen NoLa 11 112 0 09 Dec 2020
Two-phase Pseudo Label Densification for Self-training based Domain Adaptation Inkyu Shin Sanghyun Woo Fei Pan InSo Kweon 24 113 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 18 112 0 08 Dec 2020
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 101 34 0 08 Dec 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