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Robust Federated Learning with Noisy Labels

Robust Federated Learning with Noisy Labels

3 December 2020
Seunghan Yang
Hyoungseob Park
Junyoung Byun
Changick Kim
    FedML
    NoLa
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Papers citing "Robust Federated Learning with Noisy Labels"

12 / 12 papers shown
Title
Knowledge Augmentation in Federation: Rethinking What Collaborative Learning Can Bring Back to Decentralized Data
Wentai Wu
Ligang He
Saiqin Long
Ahmed M. Abdelmoniem
Yingliang Wu
Rui Mao
60
0
0
05 Mar 2025
Data Quality Control in Federated Instruction-tuning of Large Language Models
Data Quality Control in Federated Instruction-tuning of Large Language Models
Yaxin Du
Rui Ye
Fengting Yuchi
W. Zhao
Jingjing Qu
Yunhong Wang
Siheng Chen
ALM
FedML
51
0
0
15 Oct 2024
On ADMM in Heterogeneous Federated Learning: Personalization,
  Robustness, and Fairness
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness
Shengkun Zhu
Jinshan Zeng
Sheng Wang
Yuan Sun
Xiaodong Li
Yuan Yao
Zhiyong Peng
52
0
0
23 Jul 2024
Federated Active Learning Framework for Efficient Annotation Strategy in
  Skin-lesion Classification
Federated Active Learning Framework for Efficient Annotation Strategy in Skin-lesion Classification
Zhipeng Deng
Yuqiao Yang
Kenji Suzuki
MedIm
FedML
54
1
0
17 Jun 2024
Taming Cross-Domain Representation Variance in Federated Prototype
  Learning with Heterogeneous Data Domains
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
Lei Wang
Jieming Bian
Letian Zhang
Cheng Chen
Jie Xu
34
7
0
14 Mar 2024
Heterogeneous Federated Learning: State-of-the-art and Research
  Challenges
Heterogeneous Federated Learning: State-of-the-art and Research Challenges
Mang Ye
Xiuwen Fang
Bo Du
PongChi Yuen
Dacheng Tao
FedML
AAML
39
244
0
20 Jul 2023
FedNoisy: Federated Noisy Label Learning Benchmark
FedNoisy: Federated Noisy Label Learning Benchmark
Siqi Liang
Jintao Huang
Junyuan Hong
Dun Zeng
Jiayu Zhou
Zenglin Xu
FedML
40
7
0
20 Jun 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
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning
Sangmook Kim
Wonyoung Shin
Soohyuk Jang
Hwanjun Song
Se-Young Yun
31
2
0
03 May 2022
Federated Noisy Client Learning
Federated Noisy Client Learning
Huazhu Fu
Li Li
Bo Han
Chengzhong Xu
Ling Shao
FedML
23
26
0
24 Jun 2021
Combating noisy labels by agreement: A joint training method with
  co-regularization
Combating noisy labels by agreement: A joint training method with co-regularization
Hongxin Wei
Lei Feng
Xiangyu Chen
Bo An
NoLa
319
498
0
05 Mar 2020
Curriculum Loss: Robust Learning and Generalization against Label
  Corruption
Curriculum Loss: Robust Learning and Generalization against Label Corruption
Yueming Lyu
Ivor W. Tsang
NoLa
61
172
0
24 May 2019
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