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Research

Results for Federated learning

Publications & Outputs

  1. Human-in-the-Loop Learning with LLMs for Efficient RASE Tagging in Building Compliance Regulations

    Al-Turki, D., Hettiarachchi, H., Gaber, M. M., Abdelsamea, M. M., Basurra, S., Iranmanesh, S., Saadany, H. & Vakaj, E., 31/12/2024, In: IEEE Access. 12, p. 185291-185306 16 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  2. A Federated Deep Learning Framework for Privacy-Preserving Consumer Electronics Recommendations

    Wu, J., Zhang, J., Bilal, M., Han, F., Victor, N. & Xu, X., 29/02/2024, In: IEEE Transactions on Consumer Electronics. 70, 1, p. 2628 - 2638 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Edge Data Caching With Consumer-Centric Service Prediction in Resilient Industry 5.0

    Liu, G., Bao, G., Bilal, M., Jones, A., Jing, Z. & Xu, X., 29/02/2024, In: IEEE Transactions on Consumer Electronics. 70, 1, p. 1482 - 1492

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph

    Lu, Y., Yu, Z. & Suri, N., 31/08/2023, In: ACM Transactions on Privacy and Security. 26, 3, p. 1-39 39 p., 33.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  5. MSEs Credit Risk Assessment Model Based on Federated Learning and Feature Selection

    Xu, Z., Cheng, J., Cheng, L., Xu, X. & Bilal, M., 29/04/2023, In: Computers, Materials and Continua. 75, 3, p. 5573-5595 23 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. On the Design of Federated Learning in Latency and Energy Constrained Computation Offloading Operations in Vehicular Edge Computing Systems

    Shinde, S. S., Bozorgchenani, A., Tarchi, D. & Ni, Q., 28/02/2022, In: IEEE Transactions on Vehicular Technology. 71, 2, p. 2041-2057 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. Resource Allocation for Latency-aware Federated Learning in Industrial Internet-of-Things

    Gao, W., Zhao, Z., Min, G., Ni, Q. & Jiang, Y., 31/12/2021, In: IEEE Transactions on Industrial Informatics. 17, 12, p. 8505-8513 9 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review