The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.

The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.

<p>The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.</p>

Gorde:

Xehetasun bibliografikoak
Egile nagusia:	Pan Wang (198097) (author)
Beste egile batzuk:	Zhengyi Zhong (22057223) (author), Ji Wang (137458) (author)
Argitaratua:	2025
Gaiak:	Biotechnology Cancer Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified training machine learning superior privacy protection show superior performance garnered significant attention federated learning </ encoding client ids evolutionary algorithm </ diverse data distributions distributed computing framework different data distributions optimizing client selection base models </ identify base models client models base models random selection evolutionary operations identically distributed world scenarios typical fl todaynews datasets sufficiently demonstrate slower convergence randomly selected proposed method performs well method addresses lower accuracy low efficiency iid ). global model fl frameworks fl ), conduct experiments
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Izan zaitez lehena ohar bat uzten!