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Which Strategies Matter for Noisy Label Classification? Insight into
  Loss and Uncertainty

Which Strategies Matter for Noisy Label Classification? Insight into Loss and Uncertainty

14 August 2020
Wonyoung Shin
Jung-Woo Ha
Shengzhe Li
Yongwoo Cho
Hoyean Song
Sunyoung Kwon
    NoLa
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Papers citing "Which Strategies Matter for Noisy Label Classification? Insight into Loss and Uncertainty"

3 / 3 papers shown
Title
QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis
QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis
Junlin Hou
Jilan Xu
Rui Feng
Hao Chen
23
0
0
08 Apr 2024
Understanding Difficulty-based Sample Weighting with a Universal
  Difficulty Measure
Understanding Difficulty-based Sample Weighting with a Universal Difficulty Measure
Xiaoling Zhou
Ou Wu
Weiyao Zhu
Ziyang Liang
27
2
0
12 Jan 2023
Exploring the Learning Difficulty of Data Theory and Measure
Exploring the Learning Difficulty of Data Theory and Measure
Weiyao Zhu
Ou Wu
Fengguang Su
Yingjun Deng
32
5
0
16 May 2022
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