A Personalized Quantum Federated Learning

被引：0

作者：

Gurung, Dev ^{[1
]}

Pokhrel, Shiva Raj ^{[1
]}

机构：

[1] Deakin Univ Melbourne, IoT & SE Lab, Melbourne, Vic, Australia

来源：

PROCEEDINGS OF THE 8TH ASIA-PACIFIC WORKSHOP ON NETWORKING, APNET 2024 | 2024年

关键词：

D O I：

10.1145/3663408.3665806

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We develop a novel method by combining weighted personalization with quantum federated averaging to address impending challenges such as non-IID data distribution and client drift. The proposed weighted personalized Quantum Federated Learning (wpQFL) dynamically adapts to data heterogeneity, improving performance, validated through theoretical insights and empirical observations.

引用

页码：175 / 176

页数：2

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