Nov 23, 2023 · To address the resource-constrained problem in mobile computing systems, we present a novel heterogeneous FL approach named. AdapterFL, which ...
Nov 23, 2023 · Title:AdapterFL: Adaptive Heterogeneous Federated Learning for Resource-constrained Mobile Computing Systems ; Subjects: Machine Learning (cs.LG).
To address these issues, this paper introduces an effective FL approach named AdaptiveFL based on a novel fine-grained width-wise model pruning ...
Missing: AdapterFL: Mobile
AdapterFL: Adaptive Heterogeneous Federated Learning for Resource-constrained Mobile Computing Systems. R Liu, M Hu, Z Xia, J Xia, P Zhang, Y Huang, Y Liu, M ...
AdapterFL: Adaptive Heterogeneous Federated Learning for Resource-constrained Mobile Computing Systems ... learning. Federated Learning · Paper · Add Code · EqGAN ...
Federated Learning (FL) enables collaborative learning of large-scale distributed clients without data sharing. However, due to the disparity of computing ...
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We propose an FCL training strategy for new tasks, which involves adapting a specific portion of the model structure dedicated to the new task. This approach ...
Missing: AdapterFL: | Show results with:AdapterFL:
To address the resource-constrained problem in mobile computing systems, we present a novel heterogeneous FL approach named AdapterFL, which uses a model ...
Apr 27, 2024 · The experimentation results show that our proposed approach performs near to the optimum with various machine learning models and different data ...
Missing: AdapterFL: | Show results with:AdapterFL:
Nov 22, 2022 · AdapterFL: Adaptive Heterogeneous Federated Learning for Resource-constrained Mobile Computing Systems · Computer Science, Engineering. arXiv.org.