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 / 284 papers shown

Title
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler Zhining Liu Pengfei Wei Jing Jiang Wei Cao Jiang Bian Yi-Ju Chang 16 62 0 17 Oct 2020
Semi-Supervised Node Classification by Graph Convolutional Networks and Extracted Side Information Mohammadjafar Esmaeili Aria Nosratinia GNN 19 1 0 29 Sep 2020
P-DIFF: Learning Classifier with Noisy Labels based on Probability Difference Distributions Wei Hu QiHao Zhao Yangyu Huang Fan Zhang 17 5 0 14 Sep 2020
Weakly Supervised Learning with Side Information for Noisy Labeled Images Lele Cheng Xiangzeng Zhou Liming Zhao Dangwei Li Hong Shang Yun Zheng Pan Pan Yinghui Xu NoLa 36 43 0 25 Aug 2020
Data-driven Meta-set Based Fine-Grained Visual Classification Chuanyi Zhang Yazhou Yao Xiangbo Shu Zechao Li Zhenmin Tang Qi Wu NoLa 21 2 0 06 Aug 2020
Learning to Purify Noisy Labels via Meta Soft Label Corrector Yichen Wu Jun Shu Qi Xie Qian Zhao Deyu Meng 14 65 0 03 Aug 2020
Reliable Label Bootstrapping for Semi-Supervised Learning Paul Albert Diego Ortego Eric Arazo Noel E. O'Connor Kevin McGuinness SSL 21 5 0 23 Jul 2020
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning Jaehyung Kim Youngbum Hur Sejun Park Eunho Yang Sung Ju Hwang Jinwoo Shin 17 160 0 17 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 24 963 0 16 Jul 2020
Improving Face Recognition by Clustering Unlabeled Faces in the Wild Aruni RoyChowdhury Xiang Yu Kihyuk Sohn Erik Learned-Miller Manmohan Chandraker CVBM 25 19 0 14 Jul 2020
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise Amirmasoud Ghiassi Taraneh Younesian Robert Birke L. Chen NoLa 21 5 0 13 Jul 2020
ExpertNet: Adversarial Learning and Recovery Against Noisy Labels Amirmasoud Ghiassi Robert Birke Rui Han L. Chen NoLa 21 2 0 10 Jul 2020
Tilted Empirical Risk Minimization Tian Li Ahmad Beirami Maziar Sanjabi Virginia Smith 16 128 0 02 Jul 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 22 555 0 30 Jun 2020
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels Songhua Wu Xiaobo Xia Tongliang Liu Bo Han Biwei Huang Nannan Wang Haifeng Liu Gang Niu NoLa 16 53 0 14 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels Jun Shu Qian Zhao Zengben Xu Deyu Meng NoLa 31 29 0 10 Jun 2020
Learning with Weak Supervision for Email Intent Detection Kai Shu Subhabrata Mukherjee Guoqing Zheng Ahmed Hassan Awadallah Milad Shokouhi S. Dumais 16 34 0 26 May 2020
ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks Xinshao Wang Yang Hua Elyor Kodirov David A. Clifton N. Robertson NoLa 24 60 0 07 May 2020
Deep k-NN for Noisy Labels Dara Bahri Heinrich Jiang Maya R. Gupta NoLa 8 80 0 26 Apr 2020
Deep Learning Classification With Noisy Labels Guillaume Sanchez V. Guis R. Marxer F. Bouchara NoLa 14 1 0 23 Apr 2020
Self-Learning with Rectification Strategy for Human Parsing Tao Li Zhiyuan Liang Sanyuan Zhao Jiahao Gong Jianbing Shen 34 35 0 17 Apr 2020
Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise Michał Koziarski Michal Wo'zniak Bartosz Krawczyk 19 113 0 07 Apr 2020
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News Kai Shu Guoqing Zheng Yichuan Li Subhabrata Mukherjee Ahmed Hassan Awadallah Scott W. Ruston Huan Liu 30 53 0 03 Apr 2020
Robust and On-the-fly Dataset Denoising for Image Classification Jiaming Song Lunjia Hu Michael Auli Yann N. Dauphin Tengyu Ma NoLa OOD 18 13 0 24 Mar 2020
Label Noise Types and Their Effects on Deep Learning G. Algan ilkay Ulusoy NoLa 8 53 0 23 Mar 2020
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis Ruifeng Shi Deming Zhai Xianming Liu Junjun Jiang Wen Gao NoLa 14 7 0 17 Mar 2020
Improving Training on Noisy Stuctured Labels Abubakar Abid James Zou NoLa 8 1 0 08 Mar 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 24 78 0 24 Feb 2020
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights Hrayr Harutyunyan Kyle Reing Greg Ver Steeg Aram Galstyan NoLa 11 54 0 19 Feb 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 38 1,010 0 18 Feb 2020
Learning Adaptive Loss for Robust Learning with Noisy Labels Jun Shu Qian Zhao Keyu Chen Zongben Xu Deyu Meng NoLa OOD 19 23 0 16 Feb 2020
A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data Jun Hou Tong Qin Kailiang Wu D. Xiu 9 0 0 11 Feb 2020
Identifying Mislabeled Data using the Area Under the Margin Ranking Geoff Pleiss Tianyi Zhang Ethan R. Elenberg Kilian Q. Weinberger NoLa 43 261 0 28 Jan 2020
Overcoming Noisy and Irrelevant Data in Federated Learning Tiffany Tuor Shiqiang Wang Bongjun Ko Changchang Liu K. Leung FedML 6 23 0 22 Jan 2020
Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement Lan-Zhe Guo Feng Kuang Zhang-Xun Liu Yu-Feng Li Nan Ma X. Qie NoLa 9 3 0 19 Jan 2020
Towards Robust Learning with Different Label Noise Distributions Diego Ortego Eric Arazo Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 14 24 0 18 Dec 2019
Identifying Mislabeled Instances in Classification Datasets Nicolas M. Muller Karla Markert 12 49 0 11 Dec 2019
Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey G. Algan ilkay Ulusoy NoLa VLM 27 323 0 11 Dec 2019
Robust Deep Graph Based Learning for Binary Classification Minxiang Ye V. Stanković L. Stanković Gene Cheung OOD 31 10 0 06 Dec 2019
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis Davood Karimi Haoran Dou Simon K. Warfield Ali Gholipour NoLa 24 535 0 05 Dec 2019
Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels Lu Jiang Di Huang Mason Liu Weilong Yang NoLa 16 3 0 21 Nov 2019
RAD: On-line Anomaly Detection for Highly Unreliable Data Zilong Zhao Robert Birke Rui Han Bogdan Robu S. Bouchenak Sonia Ben Mokhtar L. Chen AAML 17 6 0 11 Nov 2019
Meta Label Correction for Noisy Label Learning Guoqing Zheng Ahmed Hassan Awadallah S. Dumais NoLa OffRL 24 178 0 10 Nov 2019
Confident Learning: Estimating Uncertainty in Dataset Labels Curtis G. Northcutt Lu Jiang Isaac L. Chuang NoLa 43 674 0 31 Oct 2019
Robust Training with Ensemble Consensus Jisoo Lee Sae-Young Chung NoLa 22 28 0 22 Oct 2019
Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels Lukas Lange Michael A. Hedderich Dietrich Klakow NoLa 17 15 0 14 Oct 2019
Distilling Effective Supervision from Severe Label Noise Zizhao Zhang Han Zhang Sercan Ö. Arik Honglak Lee Tomas Pfister NoLa 11 2 0 01 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 27 92 0 29 Sep 2019
Data Valuation using Reinforcement Learning Jinsung Yoon Sercan Ö. Arik Tomas Pfister TDI 27 173 0 25 Sep 2019
Anchor Loss: Modulating Loss Scale based on Prediction Difficulty Serim Ryou Seong-Gyun Jeong Pietro Perona 19 43 0 24 Sep 2019