BriefGPT.xyz
Dec, 2023
多层原型的动态异构联邦学习
Dynamic Heterogeneous Federated Learning with Multi-Level Prototypes
HTML
PDF
Shunxin Guo, Hongsong Wang, Xin Geng
TL;DR
提出了一种名为Federated Multi-Level Prototypes (FedMLP) 的新型联邦学习框架,以应对异构数据分布和动态任务的联邦学习需求,并引入原型和语义原型来缓解概念漂移问题。
Abstract
federated learning
shows promise as a privacy-preserving collaborative learning technique. Existing heterogeneous
federated learning
mainly focuses on skewing the label distribution across clients. However, most
→