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- [1] Client Selection and Resource Allocation via Graph Neural Networks for Efficient Federated Learning in Healthcare Environments 17TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS, PETRA 2024, 2024, : 606 - 612
- [2] Joint Client Selection and Resource Allocation for Federated Learning in Mobile Edge Networks 2022 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2022, : 1218 - 1223
- [3] Joint Client Selection and Privacy Compensation for Differentially Private Federated Learning IEEE INFOCOM 2024-IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS, INFOCOM WKSHPS 2024, 2024,
- [4] POWER ALLOCATION FOR WIRELESS FEDERATED LEARNING USING GRAPH NEURAL NETWORKS 2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2022, : 5243 - 5247
- [6] Client Selection with Bandwidth Allocation in Federated Learning 2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2021,
- [8] Device Selection and Resource Allocation for Layerwise Federated Learning in Wireless Networks IEEE SYSTEMS JOURNAL, 2022, 16 (04): : 6441 - 6444
- [9] Towards Stagewise and Energy-Accuracy-balanced Client Selection and Resource Allocation over Dynamic Federated Learning Networks 2024 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA, ICCC, 2024,