Subgradient Descent Learning Over Fading Multiple Access Channels With Over-the-Air Computation-Reference-Cited by-同舟云学术

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Subgradient Descent Learning Over Fading Multiple Access Channels With Over-the-Air Computation

Published:2023 Issue: Volume:11 Page:94623-94635
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Gez Tamir L. S.¹,Cohen Kobi¹^ORCID

Affiliation:

1. School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Be’er Sheva, Israel

Funder

Israel Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10168898.pdf?arnumber=10168898

Reference60 articles.

1. Active Hypothesis Testing for Anomaly Detection

2. The million song dataset;bertin-mahieux;Proc 12th Int Conf Music Inf Retr (ISMIR),2011

3. Single-Transmission Distributed Detection via Order Statistics

4. On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression

5. Active Anomaly Detection in Heterogeneous Processes

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Federated Learning from Heterogeneous Data via Controlled Air Aggregation with Bayesian Estimation;IEEE Transactions on Signal Processing;2024

2. Subgradient Descent Learning with Over-the-Air Computation;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

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