Learning to Rectify for Robust Learning with Noisy Labels

8 November 2021

Papers citing "Learning to Rectify for Robust Learning with Noisy Labels"

50 / 53 papers shown

Title
Augmentation Strategies for Learning with Noisy Labels Kento Nishi Yi Ding Alex Rich Tobias Höllerer NoLa 62 118 0 03 Mar 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise Zhaowei Zhu Tongliang Liu Yang Liu NoLa 69 129 0 22 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 151 34 0 08 Dec 2020
Learning to Learn Variational Semantic Memory Xiantong Zhen Yingjun Du Huan Xiong Qiang Qiu Cees G. M. Snoek Ling Shao SSL BDL VLM DRL 61 36 0 20 Oct 2020
Learning to Purify Noisy Labels via Meta Soft Label Corrector Yichen Wu Jun Shu Qi Xie Qian Zhao Deyu Meng 42 67 0 03 Aug 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 104 568 0 30 Jun 2020
Part-dependent Label Noise: Towards Instance-dependent Label Noise Xiaobo Xia Tongliang Liu Bo Han Nannan Wang Biwei Huang Haifeng Liu Gang Niu Dacheng Tao Masashi Sugiyama NoLa 59 67 0 14 Jun 2020
Learning to Learn Kernels with Variational Random Features Xiantong Zhen Hao Sun Yingjun Du Jun Xu Yilong Yin Ling Shao Cees G. M. Snoek DRL 72 34 0 11 Jun 2020
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models Karishma Sharma Pinar E. Donmez Enming Luo Yan Liu I. Z. Yalniz NoLa 114 34 0 15 Mar 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 358 519 0 05 Mar 2020
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights Hrayr Harutyunyan Kyle Reing Greg Ver Steeg Aram Galstyan NoLa 46 56 0 19 Feb 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 107 1,034 0 18 Feb 2020
MetaFun: Meta-Learning with Iterative Functional Updates Jin Xu Jean-François Ton Hyunjik Kim Adam R. Kosiorek Yee Whye Teh 70 68 0 05 Dec 2019
Meta Label Correction for Noisy Label Learning Guoqing Zheng Ahmed Hassan Awadallah S. Dumais NoLa OffRL 104 184 0 10 Nov 2019
L_DMI: An Information-theoretic Noise-robust Loss Function Yilun Xu Peng Cao Yuqing Kong Yizhou Wang NoLa 64 57 0 08 Sep 2019
Meta-Learning with Warped Gradient Descent Sebastian Flennerhag Andrei A. Rusu Razvan Pascanu Francesco Visin Hujun Yin R. Hadsell 98 210 0 30 Aug 2019
Deep Self-Learning From Noisy Labels Jiangfan Han Ping Luo Xiaogang Wang NoLa 69 282 0 06 Aug 2019
Are Anchor Points Really Indispensable in Label-Noise Learning? Xiaobo Xia Tongliang Liu N. Wang Bo Han Chen Gong Gang Niu Masashi Sugiyama NoLa 73 381 0 01 Jun 2019
Unsupervised Label Noise Modeling and Loss Correction Eric Arazo Sanchez Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 90 615 0 25 Apr 2019
Wasserstein Adversarial Regularization (WAR) on label noise Kilian Fatras B. Bushan Sylvain Lobry Rémi Flamary D. Tuia Nicolas Courty 51 25 0 08 Apr 2019
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels Kun Yi Jianxin Wu NoLa 68 418 0 19 Mar 2019
Noisy multi-label semi-supervised dimensionality reduction Karl Øyvind Mikalsen C. Soguero-Ruíz F. Bianchi Robert Jenssen NoLa 60 37 0 20 Feb 2019
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion Ryutaro Tanno A. Saeedi S. Sankaranarayanan Daniel C. Alexander N. Silberman NoLa 84 232 0 10 Feb 2019
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module Tiago Ramalho M. Garnelo BDL 112 77 0 07 Feb 2019
How does Disagreement Help Generalization against Label Corruption? Xingrui Yu Bo Han Jiangchao Yao Gang Niu Ivor W. Tsang Masashi Sugiyama NoLa 76 787 0 14 Jan 2019
Learning to Learn from Noisy Labeled Data Junnan Li Yongkang Wong Qi Zhao Mohan Kankanhalli NoLa 62 334 0 13 Dec 2018
Meta-Learning with Latent Embedding Optimization Andrei A. Rusu Dushyant Rao Jakub Sygnowski Oriol Vinyals Razvan Pascanu Simon Osindero R. Hadsell 144 1,372 0 16 Jul 2018
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 273 672 0 07 Jun 2018
Dimensionality-Driven Learning with Noisy Labels Xingjun Ma Yisen Wang Michael E. Houle Shuo Zhou S. Erfani Shutao Xia S. Wijewickrema James Bailey NoLa 78 434 0 07 Jun 2018
Meta-Learning Probabilistic Inference For Prediction Jonathan Gordon J. Bronskill Matthias Bauer Sebastian Nowozin Richard Turner BDL 120 265 0 24 May 2018
Masking: A New Perspective of Noisy Supervision Bo Han Jiangchao Yao Gang Niu Mingyuan Zhou Ivor Tsang Ya Zhang Masashi Sugiyama NoLa 73 255 0 21 May 2018
Meta-learning with differentiable closed-form solvers Luca Bertinetto João F. Henriques Philip Torr Andrea Vedaldi ODL 100 930 0 21 May 2018
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels Zhilu Zhang M. Sabuncu NoLa 85 2,610 0 20 May 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han Quanming Yao Xingrui Yu Gang Niu Miao Xu Weihua Hu Ivor Tsang Masashi Sugiyama NoLa 120 2,078 0 18 Apr 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 149 1,431 0 24 Mar 2018
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise Dan Hendrycks Mantas Mazeika Duncan Wilson Kevin Gimpel NoLa 134 556 0 14 Feb 2018
Robust Loss Functions under Label Noise for Deep Neural Networks Aritra Ghosh Himanshu Kumar P. Sastry NoLa OOD 78 959 0 27 Dec 2017
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 126 1,456 0 14 Dec 2017
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise Kuang-Huei Lee Xiaodong He Lei Zhang Linjun Yang NoLa 76 458 0 20 Nov 2017
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm Chelsea Finn Sergey Levine SSL 96 223 0 31 Oct 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 289 9,803 0 25 Oct 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 128 1,825 0 16 Jun 2017
Decoupling "when to update" from "how to update" Eran Malach Shai Shalev-Shwartz NoLa 95 568 0 08 Jun 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 829 11,943 0 09 Mar 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 165 1,141 0 23 Jan 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 348 4,635 0 10 Nov 2016
Deep Label Distribution Learning with Label Ambiguity Bin-Bin Gao Chao Xing Chen-Wei Xie Jianxin Wu Xin Geng 60 428 0 06 Nov 2016
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 375 7,333 0 13 Jun 2016
Cost Sensitive Learning of Deep Feature Representations from Imbalanced Data Salman H. Khan Munawar Hayat Bennamoun Ferdous Sohel R. Togneri 74 885 0 14 Aug 2015
Webly Supervised Learning of Convolutional Networks Xinlei Chen Abhinav Gupta SSL 86 373 0 07 May 2015