Federated Unlearning: A Survey on Methods, Design Guidelines, and Evaluation Metrics

IF 10.2 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE transactions on neural networks and learning systems Pub Date : 2024-10-25 DOI:10.1109/tnnls.2024.3478334

Nicolò Romandini, Alessio Mora, Carlo Mazzocca, Rebecca Montanari, Paolo Bellavista

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Federated Unlearning：关于方法、设计指南和评估指标的调查

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE transactions on neural networks and learning systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

CiteScore

23.80

自引率

9.60%

发文量

2102

审稿时长

3-8 weeks

期刊介绍： The focus of IEEE Transactions on Neural Networks and Learning Systems is to present scholarly articles discussing the theory, design, and applications of neural networks as well as other learning systems. The journal primarily highlights technical and scientific research in this domain.