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DST: Data Selection and joint Training for Learning with Noisy Labels

DST: Data Selection and joint Training for Learning with Noisy Labels

1 March 2021
Yi Wei
Xue Mei
Xin Liu
Pengxiang Xu
    NoLa
ArXiv (abs)PDFHTML

Papers citing "DST: Data Selection and joint Training for Learning with Noisy Labels"

3 / 3 papers shown
Title
FINE Samples for Learning with Noisy Labels
FINE Samples for Learning with Noisy LabelsNeural Information Processing Systems (NeurIPS), 2021
Taehyeon Kim
Jongwoo Ko
Sangwook Cho
J. Choi
Se-Young Yun
NoLa
193
114
0
23 Feb 2021
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning
Zhuowei Wang
Jing Jiang
Bo Han
Lei Feng
Bo An
Gang Niu
Guodong Long
NoLa
109
18
0
02 Dec 2020
Combating noisy labels by agreement: A joint training method with
  co-regularization
Combating noisy labels by agreement: A joint training method with co-regularizationComputer Vision and Pattern Recognition (CVPR), 2020
Jianguo Huang
Lei Feng
Xiangyu Chen
Bo An
NoLa
719
596
0
05 Mar 2020
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