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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:

A Systematic Literature Review on Client Selection in Federated Learning
Carl Smestad, Jingyue Li
(2023), pp. 2-11
Open Access | Times Cited: 14

Showing 14 citing articles:

AdaFL: Adaptive Client Selection and Dynamic Contribution Evaluation for Efficient Federated Learning
Qingming Li, Xiaohang Li, Li Zhou, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2024)
Closed Access | Times Cited: 5
A comprehensive survey on client selection strategies in federated learning
Jian Li, Tongbao Chen, Shaohua Teng
Computer Networks (2024) Vol. 251, pp. 110663-110663
Closed Access | Times Cited: 5
Client Selection in Hierarchical Federated Learning
Silvana Trindade, Nelson L. S. da Fonseca
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 17, pp. 28480-28495
Closed Access | Times Cited: 1
A Review on Research Trends of Optimization for Client Selection in Federated Learning
Jaemin Kim, Chihyun Song, Jeongyeup Paek, et al.
2022 International Conference on Information Networking (ICOIN) (2024), pp. 287-289
Closed Access | Times Cited: 1
Adaptive client selection and model aggregation for heterogeneous federated learning
Rui Zhai, Haozhe Jin, Wei Gong, et al.
Multimedia Systems (2024) Vol. 30, Iss. 4
Closed Access | Times Cited: 1
Adaptive Asynchronous Split Federated Learning for Medical Image Segmentation
Chamani Shiranthika, Hadi Hadizadeh, Parvaneh Saeedi, et al.
IEEE Access (2024) Vol. 12, pp. 182496-182515
Open Access | Times Cited: 1
Smart client selection strategies for enhanced federated learning in digital healthcare applications
D N Sachin, B. Annappa, Sateesh Ambesange
Multimedia Tools and Applications (2024)
Closed Access
GWO-Boosted Multi-Attribute Client Selection for Over- The-Air Federated Learning
Maryam Ben Driss, Essaïd Sabir, Halima Elbiaze, et al.
(2024), pp. 62-69
Open Access
DEVELOPING PRIVACY-PRESERVING FEDERATED LEARNING MODELS FOR COLLABORATIVE HEALTH DATA ANALYSIS ACROSS MULTIPLE INSTITUTIONS WITHOUT COMPROMISING DATA SECURITY
Basirat Oyekan
Journal of Knowledge Learning and Science Technology ISSN 2959-6386 (online) (2024) Vol. 3, Iss. 3, pp. 139-164
Open Access
A Robust Client Selection Mechanism for Federated Learning Environments
Rafael Veiga, John Philip Sousa, Renan Morais, et al.
Journal of the Brazilian Computer Society (2024) Vol. 30, Iss. 1, pp. 444-455
Open Access
MESFLA: Model Efficiency through Selective Federated Learning Algorithm
Alex Barros, Rafael Veiga, Renan Morais, et al.
Journal of Internet Services and Applications (2024) Vol. 15, Iss. 1, pp. 495-507
Open Access
Client Selection Mechanism for Federated Learning Based on Class Imbalance
Linlin Zhang, C. X. Lin, Zhangshuai Bie, et al.
Lecture notes in computer science (2024), pp. 266-278
Closed Access
Integrating Explainable AI with Federated Learning for Next-Generation IoT: A comprehensive review and prospective insights
Praveer Dubey, Mohit Kumar
Computer Science Review (2024) Vol. 56, pp. 100697-100697
Closed Access
Clustering-Based Federated Learning for Heterogeneous IoT Data
Shu-Min Li, Linna Wei, Weidong Zhang, et al.
(2023), pp. 172-179
Closed Access
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