Работы, цитирующие эту работу

Работ: 3

Работа: Trustworthy Federated Learning: A Comprehensive Review, Architecture, Key Challenges, and Future Research Prospects

1. Meta-XPFL: An Explainable and Personalized Federated Meta-Learning Framework for Privacy-Aware IoMT

   Mohamed Adel Serhani, Asadullah Tariq, Tariq Qayyum +3

   СтатьяPrivacy-Preserving Technologies in DataIEEE Internet of Things Journal2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2026.other.131081

2. DHFL: Decentralized Hierarchical Federated Learning With Dynamic Global Aggregation for Privacy-Aware Fog Computing

   Tariq Qayyum, Zouheir Trabelsi, Asad Waqar Malik +2

   СтатьяPrivacy-Preserving Technologies in DataIEEE Transactions on Consumer Electronics2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.005518

3. AI-Driven Lightweight and Trustworthy Federated Learning Framework for Decision-Making in Resource-Constrained Edge-IoT

   Asadullah Tariq, Farag Sallabi, Mohamed Adel Serhani +4

   СтатьяPrivacy-Preserving Technologies in DataIEEE Transactions on Consumer Electronics2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.009551