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2210.04578
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Is your noise correction noisy? PLS: Robustness to label noise with two stage detection
10 October 2022
Paul Albert
Eric Arazo
Tarun Kirshna
Noel E. O'Connor
Kevin McGuinness
NoLa
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Papers citing
"Is your noise correction noisy? PLS: Robustness to label noise with two stage detection"
8 / 8 papers shown
Title
Open set label noise learning with robust sample selection and margin-guided module
Yuandi Zhao
Qianxi Xia
Yang Sun
Zhijie Wen
Liyan Ma
Shihui Ying
NoLa
44
0
0
08 Jan 2025
Label Noise: Ignorance Is Bliss
Yilun Zhu
Jianxin Zhang
Aditya Gangrade
Clayton Scott
NoLa
26
0
0
31 Oct 2024
One-step Noisy Label Mitigation
Hao Li
Jiayang Gu
Jingkuan Song
An Zhang
Lianli Gao
NoLa
24
0
0
02 Oct 2024
An accurate detection is not all you need to combat label noise in web-noisy datasets
Paul Albert
Jack Valmadre
Eric Arazo
Tarun Krishna
Noel E. O'Connor
Kevin McGuinness
AAML
36
0
0
08 Jul 2024
Unleashing the Potential of Open-set Noisy Samples Against Label Noise for Medical Image Classification
Zehui Liao
Shishuai Hu
Yong-quan Xia
33
0
0
18 Jun 2024
Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels
Ke Wang
Guillermo Ortiz-Jimenez
Rodolphe Jenatton
Mark Collier
Efi Kokiopoulou
Pascal Frossard
AAML
19
2
0
10 Oct 2023
Manifold DivideMix: A Semi-Supervised Contrastive Learning Framework for Severe Label Noise
Fahimeh Fooladgar
Minh Nguyen Nhat To
P. Mousavi
Purang Abolmaesumi
NoLa
24
4
0
13 Aug 2023
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
Bowen Zhang
Yidong Wang
Wenxin Hou
Hao Wu
Jindong Wang
Manabu Okumura
T. Shinozaki
AAML
218
861
0
15 Oct 2021
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