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Making Deep Neural Networks Robust to Label Noise: a Loss Correction
  Approach

Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

13 September 2016
Giorgio Patrini
A. Rozza
A. Menon
Richard Nock
Lizhen Qu
    NoLa
ArXivPDFHTML

Papers citing "Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach"

15 / 215 papers shown
Title
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels
Kun Yi
Jianxin Wu
NoLa
25
409
0
19 Mar 2019
An Effective Label Noise Model for DNN Text Classification
An Effective Label Noise Model for DNN Text Classification
Ishan Jindal
Daniel Pressel
Brian Lester
M. Nokleby
NoLa
18
48
0
18 Mar 2019
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action
  Classifier for Anomaly Detection
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection
Jia-Xing Zhong
Nannan Li
Weijie Kong
Shan Liu
Thomas H. Li
Ge Li
NoLa
SSL
13
396
0
18 Mar 2019
Learning From Noisy Labels By Regularized Estimation Of Annotator
  Confusion
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion
Ryutaro Tanno
A. Saeedi
S. Sankaranarayanan
Daniel C. Alexander
N. Silberman
NoLa
11
227
0
10 Feb 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Kimin Lee
Mantas Mazeika
NoLa
12
717
0
28 Jan 2019
Limited Gradient Descent: Learning With Noisy Labels
Limited Gradient Descent: Learning With Noisy Labels
Yi Sun
Yan Tian
Yiping Xu
Jianxiang Li
NoLa
19
13
0
20 Nov 2018
An Entropic Optimal Transport Loss for Learning Deep Neural Networks
  under Label Noise in Remote Sensing Images
An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images
B. Damodaran
Rémi Flamary
Vivien Seguy
Nicolas Courty
NoLa
8
39
0
02 Oct 2018
On the Minimal Supervision for Training Any Binary Classifier from Only
  Unlabeled Data
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
Nan Lu
Gang Niu
A. Menon
Masashi Sugiyama
MQ
22
85
0
31 Aug 2018
CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images
CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images
Sheng Guo
Weilin Huang
Haozhi Zhang
Chenfan Zhuang
Dengke Dong
Matthew R. Scott
Dinglong Huang
SSL
18
338
0
03 Aug 2018
Dimensionality-Driven Learning with Noisy Labels
Dimensionality-Driven Learning with Noisy Labels
Xingjun Ma
Yisen Wang
Michael E. Houle
Shuo Zhou
S. Erfani
Shutao Xia
S. Wijewickrema
James Bailey
NoLa
16
424
0
07 Jun 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely
  Noisy Labels
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
23
2,025
0
18 Apr 2018
Joint Optimization Framework for Learning with Noisy Labels
Joint Optimization Framework for Learning with Noisy Labels
Daiki Tanaka
Daiki Ikami
T. Yamasaki
Kiyoharu Aizawa
NoLa
14
701
0
30 Mar 2018
Learning with Biased Complementary Labels
Learning with Biased Complementary Labels
Xiyu Yu
Tongliang Liu
Mingming Gong
Dacheng Tao
24
192
0
27 Nov 2017
Transfer Learning with Label Noise
Transfer Learning with Label Noise
Xiyu Yu
Tongliang Liu
Mingming Gong
Kun Zhang
Kayhan Batmanghelich
Dacheng Tao
NoLa
8
32
0
31 Jul 2017
Learning from Binary Labels with Instance-Dependent Corruption
Learning from Binary Labels with Instance-Dependent Corruption
A. Menon
Brendan van Rooyen
Nagarajan Natarajan
NoLa
31
41
0
03 May 2016
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