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An Instance-Dependent Simulation Framework for Learning with Label Noise

An Instance-Dependent Simulation Framework for Learning with Label Noise

23 July 2021
Keren Gu
Xander Masotto
Vandana Bachani
Balaji Lakshminarayanan
Jack Nikodem
Dong Yin
    NoLa
ArXivPDFHTML

Papers citing "An Instance-Dependent Simulation Framework for Learning with Label Noise"

6 / 6 papers shown
Title
Price of Stability in Quality-Aware Federated Learning
Price of Stability in Quality-Aware Federated Learning
Yizhou Yan
Xinyu Tang
Chao Huang
Ming Tang
FedML
30
1
0
13 Oct 2023
Multi-annotator Deep Learning: A Probabilistic Framework for
  Classification
Multi-annotator Deep Learning: A Probabilistic Framework for Classification
M. Herde
Denis Huseljic
Bernhard Sick
33
9
0
05 Apr 2023
Quantifying the Impact of Label Noise on Federated Learning
Quantifying the Impact of Label Noise on Federated Learning
Shuqi Ke
Chao Huang
Xin Liu
FedML
28
7
0
15 Nov 2022
Detecting Label Errors in Token Classification Data
Detecting Label Errors in Token Classification Data
Wei-Chen Wang
Jonas W. Mueller
19
13
0
08 Oct 2022
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
950
20,572
0
17 Apr 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,675
0
05 Dec 2016
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