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Privacy‐Preserving Federated Learning: Adaptive Quantization and Layer‐Specific Differential Privacy With Client Dropout Mitigation.

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Title: Privacy‐Preserving Federated Learning: Adaptive Quantization and Layer‐Specific Differential Privacy With Client Dropout Mitigation.
Authors: Atia, Ahmad G.1, Karawia, Abdelrahman A.1,2, Fouda, Yasser M.1, El-Gayar, Mostafa M.3,4, mostafa_elgayar@mans.edu.eg, Wang, Zhaocai, zcwang1028@163.com
Source: Applied Computational Intelligence & Soft Computing; 5/30/2026, Vol. 2026, p1-16, 16p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 194204637
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Privacy‐Preserving Federated Learning: Adaptive Quantization and Layer‐Specific Differential Privacy With Client Dropout Mitigation.
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        Value: 10.1155/acis/1125376
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      – Code: eng
        Text: English
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      – TitleFull: Privacy‐Preserving Federated Learning: Adaptive Quantization and Layer‐Specific Differential Privacy With Client Dropout Mitigation.
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              Text: 5/30/2026
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              Y: 2026
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