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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:

Towards Efficient and Stable K-Asynchronous Federated Learning With Unbounded Stale Gradients on Non-IID Data
Zihao Zhou, Yanan Li, Xuebin Ren, et al.
IEEE Transactions on Parallel and Distributed Systems (2022) Vol. 33, Iss. 12, pp. 3291-3305
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Auction-Based Cluster Federated Learning in Mobile Edge Computing Systems
Renhao Lu, Weizhe Zhang, Yan Wang, et al.
IEEE Transactions on Parallel and Distributed Systems (2023) Vol. 34, Iss. 4, pp. 1145-1158
Closed Access | Times Cited: 41
Federated Learning With Non-IID Data: A Survey
Z.J. Lu, Heng Pan, Yueyue Dai, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 11, pp. 19188-19209
Closed Access | Times Cited: 38
IDS-DWKAFL: An intrusion detection scheme based on Dynamic Weighted K-asynchronous Federated Learning for smart grid
Mi Wen, Yanbo Zhang, P.Y. Zhang, et al.
Journal of Information Security and Applications (2025) Vol. 89, pp. 103993-103993
Closed Access | Times Cited: 1
FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity
Guanghao Li, Yue Hu, Miao Zhang, et al.
(2022)
Open Access | Times Cited: 26
TORR: A Lightweight Blockchain for Decentralized Federated Learning
Xuyang Ma, Du Xu
IEEE Internet of Things Journal (2023) Vol. 11, Iss. 1, pp. 1028-1040
Closed Access | Times Cited: 12
QuAsyncFL: Asynchronous Federated Learning With Quantization for Cloud–Edge–Terminal Collaboration Enabled AIoT
Ye Liu, Peishan Huang, Fan Yang, et al.
IEEE Internet of Things Journal (2023) Vol. 11, Iss. 1, pp. 59-69
Closed Access | Times Cited: 9
FedGSM: Efficient Federated Learning for LEO Constellations with Gradient Staleness Mitigation
Lingling Wu, Jingjing Zhang
(2023), pp. 356-360
Open Access | Times Cited: 9
Differentially Private Federated Learning on Non-iid Data: Convergence Analysis and Adaptive Optimization
Lin Chen, Xiaofeng Ding, Zhifeng Bao, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 9, pp. 4567-4581
Open Access | Times Cited: 3
Federated Learning with Efficient Aggregation via Markov Decision Process in Edge Networks
Tongfei Liu, Hui Wang, Maode Ma
Mathematics (2024) Vol. 12, Iss. 6, pp. 920-920
Open Access | Times Cited: 3
Multi-Stage Asynchronous Federated Learning With Adaptive Differential Privacy
Yanan Li, Shusen Yang, Xuebin Ren, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Vol. 46, Iss. 2, pp. 1243-1256
Closed Access | Times Cited: 8
Towards Efficient Asynchronous Federated Learning in Heterogeneous Edge Environments
Yajie Zhou, Xiaoyi Pang, Zhibo Wang, et al.
IEEE INFOCOM 2022 - IEEE Conference on Computer Communications (2024), pp. 2448-2457
Closed Access | Times Cited: 2
Adaptive differential privacy in asynchronous federated learning for aerial-aided edge computing
Yadong Zhang, Huixiang Zhang, Yi Yang, et al.
Journal of Network and Computer Applications (2024) Vol. 235, pp. 104087-104087
Closed Access | Times Cited: 2
Topologies in distributed machine learning: Comprehensive survey, recommendations and future directions
Ling Liu, Pan Zhou, Gang Sun, et al.
Neurocomputing (2023) Vol. 567, pp. 127009-127009
Closed Access | Times Cited: 5
Asynchronous Federated Learning for Real-Time Multiple Licence Plate Recognition Through Semantic Communication
Renyou Xie, Chaojie Li, Xiaojun Zhou, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2023), pp. 1-5
Closed Access | Times Cited: 4
Elastic Optimization for Stragglers in Edge Federated Learning
Khadija Sultana, Khandakar Ahmed, Bruce Gu, et al.
Big Data Mining and Analytics (2023) Vol. 6, Iss. 4, pp. 404-420
Open Access | Times Cited: 4
Boosting Dynamic Decentralized Federated Learning by Diversifying Model Sources
Dongyuan Su, Yipeng Zhou, Laizhong Cui, et al.
IEEE Transactions on Services Computing (2024) Vol. 17, Iss. 4, pp. 1400-1413
Closed Access | Times Cited: 1
Communication Efficiency and Non-Independent and Identically Distributed Data Challenge in Federated Learning: A Systematic Mapping Study
Basmah K. Alotaibi, Fakhri Alam Khan, Sajjad Mahmood
Applied Sciences (2024) Vol. 14, Iss. 7, pp. 2720-2720
Open Access | Times Cited: 1
Self-adaptive asynchronous federated optimizer with adversarial sharpness-aware minimization
Xiongtao Zhang, Ji Wang, Weidong Bao, et al.
Future Generation Computer Systems (2024) Vol. 161, pp. 638-654
Closed Access | Times Cited: 1
CaBaFL: Asynchronous Federated Learning via Hierarchical Cache and Feature Balance
Zeke Xia, Ming Hu, Dengke Yan, et al.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2024) Vol. 43, Iss. 11, pp. 4057-4068
Open Access | Times Cited: 1
Cloud–Edge–End Collaborative Federated Learning: Enhancing Model Accuracy and Privacy in Non-IID Environments
Ling Li, Lidong Zhu, Weibang Li
Sensors (2024) Vol. 24, Iss. 24, pp. 8028-8028
Open Access | Times Cited: 1
A decentralized asynchronous federated learning framework for edge devices
Bin Wang, Tian Zhao, Jie Ma, et al.
Future Generation Computer Systems (2024), pp. 107683-107683
Closed Access | Times Cited: 1
Enhanced Hybrid Hierarchical Federated Edge Learning Over Heterogeneous Networks
Qimei Chen, Zehua You, Dingzhu Wen, et al.
IEEE Transactions on Vehicular Technology (2023), pp. 1-15
Closed Access | Times Cited: 3
BCAFL: A Blockchain-Based Framework for Asynchronous Federated Learning Protection
Jian Yun, Yusheng Lu, Xinyu Liu
Electronics (2023) Vol. 12, Iss. 20, pp. 4214-4214
Open Access | Times Cited: 2
Optimizing Computing Efficiency and Performance Fairness in Federated Learning
Di Liao
Advances in transdisciplinary engineering (2024)
Open Access
R-FAST: Robust Fully-Asynchronous Stochastic Gradient Tracking Over General Topology
Zehan Zhu, Ye Tian, Yan Huang, et al.
IEEE Transactions on Signal and Information Processing over Networks (2024) Vol. 10, pp. 665-678
Closed Access
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