Apr 26, 2023 · Thus, this paper introduces a two-phased client selection and scheduling approach to improve the convergence speed while capturing all data ...
Abstract—Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed.
This approach ensures correct clustering and fairness between clients by leveraging bandwidth reuse for participants spent a longer time training their models ...
Jun 1, 2023 · This paper introduces a two-phased client selection and scheduling approach to improve the convergence speed while capturing all data distributions.
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What is clustered federated learning?
What is federated edge learning?
Apr 25, 2023 · 当数据不平衡并且以非独立且同分布的方式分布在客户端之间时，引入集群联合多任务学习作为一种有效的技术。虽然相似性度量可以根据客户端组的数据分布为其 ...
Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning · Hamad bin Khalifa University · Memorial University of Newfoundland.
Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning · Intelligent Model Aggregation in Hierarchical Clustered Federated ...
Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and ...
Therefore, it is imperative that a subset of clients is selected periodically due to the limited bandwidth and latency constraints at the network edge. To this ...
Jan 19, 2024 · A. Dobre, “Fair selection of edge nodes to participate in clustered federated multitask learning,” IEEE Transactions on Network and Service ...