Joint Optimization Framework for Learning with Noisy Labels

30 March 2018

Papers citing "Joint Optimization Framework for Learning with Noisy Labels"

50 / 138 papers shown

Title
MSR: Making Self-supervised learning Robust to Aggressive Augmentations Ying-Long Bai Erkun Yang Zhaoqing Wang Yuxuan Du Bo Han Cheng Deng Dadong Wang Tongliang Liu SSL 25 3 0 04 Jun 2022
Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher Jing Jiang Weihong Deng 29 23 0 28 May 2022
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning Sangmook Kim Wonyoung Shin Soohyuk Jang Hwanjun Song Se-Young Yun 29 2 0 03 May 2022
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels Yangdi Lu Wenbo He NoLa 37 39 0 02 May 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 98 0 28 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 27 4 0 21 Mar 2022
Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li Xiaobo Xia Shiming Ge Tongliang Liu NoLa 24 172 0 08 Mar 2022
Robust Training under Label Noise by Over-parameterization Sheng Liu Zhihui Zhu Qing Qu Chong You NoLa OOD 27 106 0 28 Feb 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 30 2 0 27 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 41 3 0 09 Feb 2022
Data Consistency for Weakly Supervised Learning Chidubem Arachie Bert Huang NoLa 22 2 0 08 Feb 2022
Learning with Neighbor Consistency for Noisy Labels Ahmet Iscen Jack Valmadre Anurag Arnab Cordelia Schmid NoLa 41 75 0 04 Feb 2022
Uncertainty-aware Pseudo-label Selection for Positive-Unlabeled Learning Emilio Dorigatti Jann Goschenhofer B. Schubert Mina Rezaei Bernd Bischl 23 3 0 31 Jan 2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise? Yexiong Lin Yu Yao Yuxuan Du Jun Yu Bo Han Biwei Huang Tongliang Liu NoLa 53 3 0 30 Jan 2022
DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning Chenghao Huang Weilong Chen Yuxi Chen Shunji Yang Yanru Zhang FedML 16 2 0 30 Jan 2022
Semantic Clustering based Deduction Learning for Image Recognition and Classification Wenchi Ma Xuemin Tu Bo Luo Guanghui Wang 36 29 0 25 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 30 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 31 72 0 05 Dec 2021
Federated Semi-Supervised Learning with Class Distribution Mismatch Zhiguo Wang Xintong Wang Ruoyu Sun Tsung-Hui Chang FedML 18 12 0 29 Oct 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
Noisy Annotation Refinement for Object Detection Jiafeng Mao Qing Yu Yoko Yamakata Kiyoharu Aizawa NoLa 42 10 0 20 Oct 2021
Clean or Annotate: How to Spend a Limited Data Collection Budget Derek Chen Zhou Yu Samuel R. Bowman 35 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 40 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 29 104 0 07 Oct 2021
Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction Jiarun Liu Ruirui Li Chuan Sun OOD NoLa VLM 22 32 0 11 Sep 2021
Assessing the Quality of the Datasets by Identifying Mislabeled Samples Vaibhav Pulastya Gaurav Nuti Yash Kumar Atri Tanmoy Chakraborty NoLa 27 5 0 10 Sep 2021
MetaXT: Meta Cross-Task Transfer between Disparate Label Spaces Srinagesh Sharma Guoqing Zheng Ahmed Hassan Awadallah 24 1 0 09 Sep 2021
NGC: A Unified Framework for Learning with Open-World Noisy Data Zhi-Fan Wu Tong Wei Jianwen Jiang Chaojie Mao Mingqian Tang Yu-Feng Li 11 80 0 25 Aug 2021
Co-learning: Learning from Noisy Labels with Self-supervision Cheng Tan Jun-Xiong Xia Lirong Wu Stan Z. Li NoLa 76 116 0 05 Aug 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 18 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
Distilling effective supervision for robust medical image segmentation with noisy labels Jialin Shi Ji Wu NoLa 16 32 0 21 Jun 2021
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion Xian-Jin Gui Wei Wang Zhang-Hao Tian NoLa 27 44 0 17 Jun 2021
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels Erik Englesson Hossein Azizpour NoLa 34 103 0 10 May 2021
Boosting Co-teaching with Compression Regularization for Label Noise Yingyi Chen Xin Shen S. Hu Johan A. K. Suykens NoLa 42 45 0 28 Apr 2021
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew S. Lan NoLa 21 58 0 19 Apr 2021
Learning from Noisy Labels via Dynamic Loss Thresholding Hao Yang Youzhi Jin Zi-Hua Li Deng-Bao Wang Lei Miao Xin Geng Min-Ling Zhang NoLa AI4CE 29 6 0 01 Apr 2021
Semi-Supervised Domain Adaptation via Selective Pseudo Labeling and Progressive Self-Training Yoonhyung Kim Changick Kim 13 8 0 01 Apr 2021
Jo-SRC: A Contrastive Approach for Combating Noisy Labels Yazhou Yao Zeren Sun Chuanyi Zhang Fumin Shen Qi Wu Jian Zhang Zhenmin Tang NoLa 33 133 0 24 Mar 2021
Unified Robust Training for Graph NeuralNetworks against Label Noise Yayong Li Jie Yin Ling-Hao Chen NoLa 24 29 0 05 Mar 2021
DST: Data Selection and joint Training for Learning with Noisy Labels Yi Wei Xue Mei Xin Liu Pengxiang Xu NoLa 24 3 0 01 Mar 2021
Open-World Semi-Supervised Learning Kaidi Cao Maria Brbic J. Leskovec BDL 16 177 0 06 Feb 2021
Bridging In- and Out-of-distribution Samples for Their Better Discriminability Engkarat Techapanurak Anh-Chuong Dang Takayuki Okatani OODD 25 3 0 07 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 26 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 40 122 0 10 Dec 2020
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting Hongxin Wei Lei Feng R. Wang Bo An NoLa 25 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 30 112 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 27 112 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 103 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