HIGHLIGHTS
- who: Helin Yang from the (UNIVERSITY) have published the Article: Lead federated neuromorphic learning for wireless edge artificial intelligence, in the Journal: (JOURNAL) of 17/01/2022
- what: The authors propose lead federated neuromorphic learning (LFNL), a decentralized brain-inspired computing method based on SNNs, enabling multiple edge devices to collaboratively train a global neuromorphic model without a fixed central coordinator. The aim of the leader is to aggregate the uploaded local neuromorphic model parameters (w2, w3, u2026, wK ) from the followers. The aim of the federated learning task is to find an optimal model . . .
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