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arXiv Machine Learning By Eunjeong Jeong, Nikolaos Pappas

Computation-aware Energy-harvesting Federated Learning with Pipelined Cyclic Scheduling

Read the original on arXiv Machine Learning →

arXiv:2511. 11949v2 Announce Type: replace Abstract: Federated learning (FL) is a powerful paradigm for distributed learning, but increasing model complexity leads to significant energy consumption from client-side computations for local training.

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