OpenAlex Citation Counts

OpenAlex Citations Logo

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 26-50 of 38 citing articles:

Two-stage model fusion scheme based on knowledge distillation for stragglers in federated learning
Jiuyun Xu, Xiaowen Li, Kanjie Zhu, et al.
International Journal of Machine Learning and Cybernetics (2024)
Closed Access

Accelerating Unsupervised Federated Graph Neural Networks via Semi-asynchronous Communication
Yuanming Liao, Duanji Wu, Pengyu Lin, et al.
Communications in computer and information science (2024), pp. 378-392
Closed Access

K Asynchronous Federated Learning with Cosine Similarity Based Aggregation on Non-IID Data
Shan Wu, Yizhi Zhou, Xuesong Gao, et al.
Lecture notes in computer science (2024), pp. 434-452
Closed Access

Multi-Attribute Auction-Based Grouped Federated Learning
Renhao Lu, Hongwei Yang, Yan Wang, et al.
IEEE Transactions on Services Computing (2024) Vol. 17, Iss. 3, pp. 1056-1071
Closed Access

VIFL: vulnerability identification using federated learning in the internet of things systems
Wael Issa, Nour Moustafa, Benjamin Turnbull, et al.
Computing (2024) Vol. 107, Iss. 1
Closed Access

Evolutionary cross-client network aggregation for personalized federated learning
Yuwei Fan, Wei Xi, Yuhao Shen, et al.
Knowledge-Based Systems (2024), pp. 112866-112866
Closed Access

Communication-Efficient Federated Learning for Power Load Forecasting in Electric IoTs
ZhengXiong Mao, Hui Li, Zuyuan Huang, et al.
IEEE Access (2023) Vol. 11, pp. 47930-47939
Open Access | Times Cited: 1

Design of an Efficient Multidomain Augmented Data Aggregation Model to Solve Heterogeneity Issues for IoT Deployments
Meesala Sravani, Suniti Purbey, Burada Chakradhar, et al.
(2023)
Closed Access | Times Cited: 1

Towards Hierarchical Clustered Federated Learning With Model Stability on Mobile Devices
Biyao Gong, Tianzhang Xing, Zhidan Liu, et al.
IEEE Transactions on Mobile Computing (2023) Vol. 23, Iss. 6, pp. 7148-7164
Closed Access | Times Cited: 1

Analysis and Optimization of Wireless Federated Learning With Data Heterogeneity
Xuefeng Han, Jun Li, Wen Chen, et al.
IEEE Transactions on Wireless Communications (2023) Vol. 23, Iss. 7, pp. 7728-7744
Open Access | Times Cited: 1

Differentially Private Federated Learning With Importance Client Sampling
Lin Chen, Xiaofeng Ding, Mengqi Li, et al.
IEEE Transactions on Consumer Electronics (2023) Vol. 70, Iss. 1, pp. 3635-3649
Closed Access

Integrating Staleness and Shapley Value Consistency for Efficient K-Asynchronous Federated Learning
Yuhui Jiang, Xingjian Lu, Wei Mao, et al.
2021 IEEE International Conference on Big Data (Big Data) (2023), pp. 680-689
Closed Access

Previous Page - Page 2

Scroll to top