Compute-Update Federated Learning: A Lattice Coding Approach

IF 4.6 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Signal Processing Pub Date : 2024-11-05 DOI:10.1109/tsp.2024.3491993

Seyed Mohammad Azimi-Abarghouyi, Lav R. Varshney

引用次数: 0

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计算-更新联合学习：网格编码方法

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 Signal Processing 工程技术-工程：电子与电气

CiteScore

11.20

自引率

9.30%

发文量

310

审稿时长

3.0 months

期刊介绍： The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.