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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Fed-DR-Filter: Using global data representation to reduce the impact of noisy labels on the performance of federated learning
Shaoming Duan, Chuanyi Liu, Zhengsheng Cao, et al.
Future Generation Computer Systems (2022) Vol. 137, pp. 336-348
Closed Access | Times Cited: 14

Showing 14 citing articles:

Affordable federated edge learning framework via efficient Shapley value estimation
Liguo Dong, Zhenmou Liu, Kejia Zhang, et al.
Future Generation Computer Systems (2023) Vol. 147, pp. 339-349
Closed Access | Times Cited: 15
Applications and Challenges of Federated Learning Paradigm in the Big Data Era with Special Emphasis on COVID-19
Abdul Majeed, Xiaohan Zhang, Seong Oun Hwang
Big Data and Cognitive Computing (2022) Vol. 6, Iss. 4, pp. 127-127
Open Access | Times Cited: 19
FedDSHAR: A dual-strategy federated learning approach for human activity recognition amid noise label user
Ziqian Lin, Xuefeng Jiang, Kun Zhang, et al.
Future Generation Computer Systems (2025), pp. 107724-107724
Closed Access
Continual and wisdom learning for federated learning: A comprehensive framework for robustness and debiasing
Saeed Iqbal, Xiaopin Zhong, Muhammad Attique Khan, et al.
Information Processing & Management (2025) Vol. 62, Iss. 5, pp. 104157-104157
Closed Access
Labeling Chaos to Learning Harmony: Federated Learning with Noisy Labels
Vasileios Tsouvalas, Aaqib Saeed, Tanır Özçelebi, et al.
ACM Transactions on Intelligent Systems and Technology (2023) Vol. 15, Iss. 2, pp. 1-26
Open Access | Times Cited: 9
Overhead-free Noise-tolerant Federated Learning: A New Baseline
Shiyi Lin, Deming Zhai, Feilong Zhang, et al.
Deleted Journal (2024) Vol. 21, Iss. 3, pp. 526-537
Closed Access | Times Cited: 2
On the Impact of Label Noise in Federated Learning
Shuqi Ke, Chao Huang, Xin Liu
(2023), pp. 183-190
Closed Access | Times Cited: 4
Overcoming Noisy Labels and Non-IID Data in Edge Federated Learning
Yang Xu, Yunming Liao, Lun Wang, et al.
IEEE Transactions on Mobile Computing (2024) Vol. 23, Iss. 12, pp. 11406-11421
Closed Access | Times Cited: 1
HT-Fed-GAN: Federated Generative Model for Decentralized Tabular Data Synthesis
Shaoming Duan, Chuanyi Liu, Peiyi Han, et al.
Entropy (2022) Vol. 25, Iss. 1, pp. 88-88
Open Access | Times Cited: 6
Fed-DNN-Debugger: Automatically Debugging Deep Neural Network Models in Federated Learning
Shaoming Duan, Chuanyi Liu, Peiyi Han, et al.
Security and Communication Networks (2023) Vol. 2023, pp. 1-14
Open Access | Times Cited: 3
A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward
Abdul Majeed, Seong Oun Hwang
IEEE Access (2024) Vol. 12, pp. 84643-84679
Open Access
MDD-FedGNN: A vertical federated graph learning framework for malicious domain detection
Sanfeng Zhang, Qingyu Hao, Zijian Gong, et al.
Computers & Security (2024) Vol. 147, pp. 104093-104093
Closed Access
A Survey of Graph Federation Learning for Data Privacy Security Scenarios
Guangsheng Luo, Zhijun Fang, Xiaoli Zhao, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Creating Collaborative Data Representations Using Matrix Manifold Optimal Computation and Automated Hyperparameter Tuning
Keiyu Nosaka, Akiko Yoshise
(2023) Vol. 15, pp. 180-185
Closed Access
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