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Yahia A. Eldemerdash

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Articles by Yahia A. Eldemerdash

[2510.03860] Privacy Enhancement in Over-the-Air Federated Learning via Adaptive Receive Scaling

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By Faeze Moradi, Yahia A. Eldemerdash, Ho Ting
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2501.18058] Power-Efficient Over-the-Air Aggregation with Receive Beamforming for Federated Learning

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By Faeze Moradi, Yahia A. Eldemerdash, Ho Ting
| arXiv
[Submitted on 29 Jan 2025] Title:Power-Efficient Over-the-Air Aggregation with Receive Beamforming for Federated Learning View a PDF of the paper titled Power-Efficient Over-the-Air Aggregation with Receive Beamforming for Federated Learning, by Faeze Moradi Kalarde and 4 other authors View PDF HTML (experimental) Abstract:This paper studies power-efficient uplink transmission design for federated learning (FL) that employs over-the-air analog aggregation and multi-antenna beamforming at the...
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[2302.14336] Beamforming and Device Selection Design in Federated Learning with Over-the-air Aggregation

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By Faeze Moradi, Yahia A. Eldemerdash, Ho Ting
| arXiv
[Submitted on 28 Feb 2023 ( v1 ), last revised 7 Mar 2024 (this version, v4)] Title:Beamforming and Device Selection Design in Federated Learning with Over-the-air Aggregation Download a PDF of the paper titled Beamforming and Device Selection Design in Federated Learning with Over-the-air Aggregation, by Faeze Moradi Kalarde and 4 other authors Download PDF HTML (experimental) Abstract:Federated learning (FL) with over-the-air computation can efficiently utilize the communication bandwidth...
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