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cs.LG2025
Accelerated Training on Low-Power Edge Devices
Mohamed Aboelenien Ahmed, Kilian Pfeiffer, Heba Khdr +3
Training on edge devices poses several challenges as these devices are generally resource-constrained, especially in terms of power. State-of-the-art techniques at the device level…
cs.LG2024
Training Heterogeneous Client Models using Knowledge Distillation in Serverless Federated Learning
Mohak Chadha, Pulkit Khera, Jianfeng Gu +2
Federated Learning (FL) is an emerging machine learning paradigm that enables the collaborative training of a shared global model across distributed clients while keeping the data…