Communication-efficient federated recommendation model based on many-objective evolutionary algorithm

•A novel communication-efficient federated recommendation model is proposed.•A many-objective evolutionary method is used to achieve parameter reduction.•Recommended performances and communication cost are optimized simultaneously. The federated recommendation system (FedRS), which is the applicatio...

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Vydané v:	Expert systems with applications Ročník 201; s. 116963
Hlavní autori:	Cui, Zhihua, Wen, Jie, Lan, Yang, Zhang, Zhixia, Cai, Jianghui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Ltd 01.09.2022 Elsevier BV
Predmet:	Communication Evolutionary algorithms Federated learning Federated recommendation model Genetic algorithms Many-objective evolutionary algorithm Mathematical models Optimization Performance evaluation Process parameters Recommendation system Recommender systems RVEA Many-objective evolutionary algorithm Federated learning RVEA Federated recommendation model Recommendation system
ISSN:	0957-4174, 1873-6793
On-line prístup:	Získať plný text
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