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cs.LG2025
Towards Decentralized and Sustainable Foundation Model Training with the Edge
Leyang Xue, Meghana Madhyastha, Randal Burns +2
Foundation models are at the forefront of AI research, appealing for their ability to learn from vast datasets and cater to diverse tasks. Yet, their significant computational dema…
cs.LG2024
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification
Faisal Ahmed, Myungjin Lee, Suresh Subramaniam +3
Federated Learning (FL) has garnered significant interest recently due to its potential as an effective solution for tackling many challenges in diverse application scenarios, for…