论文标题
可扩展的联合学习对被动光网络
Scalable Federated Learning over Passive Optical Networks
论文作者
论文摘要
引入了两步聚合，以促进被动光网（PON）的可扩展联合学习（SFL）。结果表明，SFL可保持所需的PON上游带宽常数，而不管涉及客户的数量多少，同时带来了约10％的学习精度。
Two-step aggregation is introduced to facilitate scalable federated learning (SFL) over passive optical networks (PONs). Results reveal that the SFL keeps the required PON upstream bandwidth constant regardless of the number of involved clients, while bringing ~10% learning accuracy improvement.
