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  • Yang X, Xiong B, Huang Y and Xu C. Cross-Modal Federated Human Activity Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 10.1109/TPAMI.2024.3367412. 46:8. (5345-5361).

    https://ieeexplore.ieee.org/document/10440498/

  • Fenoglio D, Li M, Casnici D, Laporte M, Gashi S, Santini S, Gjoreski M and Langheinrich M. (2024). Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors 2024 International Conference on Intelligent Environments (IE). 10.1109/IE61493.2024.10599924. 979-8-3503-8679-0. (17-24).

    https://ieeexplore.ieee.org/document/10599924/

  • Zhu R, Yang M and Wang Q. (2024). ShuffleFL: Addressing Heterogeneity in Multi-Device Federated Learning. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 8:2. (1-34). Online publication date: 13-May-2024.

    https://doi.org/10.1145/3659621

  • Jiang S, Shuai X and Xing G. (2024). ArtFL: Exploiting Data Resolution in Federated Learning for Dynamic Runtime Inference via Multi-Scale Training 2024 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 10.1109/IPSN61024.2024.00007. 979-8-3503-6201-5. (27-38).

    https://ieeexplore.ieee.org/document/10577356/

  • Lee C, Cho S, Park H, Park J and Lee S. (2024). GAN-Enhanced Vertical Federated Learning System for WHAR with non-IID Data NOMS 2024-2024 IEEE Network Operations and Management Symposium. 10.1109/NOMS59830.2024.10575811. 979-8-3503-2793-9. (1-5).

    https://ieeexplore.ieee.org/document/10575811/

  • Gad G, Farrag A, Aboulfotouh A, Bedda K, Fadlullah Z and Fouda M. Joint Self-Organizing Maps and Knowledge-Distillation-Based Communication-Efficient Federated Learning for Resource-Constrained UAV-IoT Systems. IEEE Internet of Things Journal. 10.1109/JIOT.2023.3349295. 11:9. (15504-15522).

    https://ieeexplore.ieee.org/document/10379499/

  • Sandhu M, Silvera-Tawil D, Lu W, Borges P and Kusy B. (2024). Exploring Activity Recognition in Multi-device Environments using Hierarchical Federated Learning 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). 10.1109/PerComWorkshops59983.2024.10503023. 979-8-3503-0436-7. (720-726).

    https://ieeexplore.ieee.org/document/10503023/

  • Li X, Liu S, Zhou Z, Guo B, Xu Y and Yu Z. (2024). EchoPFL. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 8:1. (1-22). Online publication date: 6-Mar-2024.

    https://doi.org/10.1145/3643560

  • Gong K, Gao Y and Dong W. (2024). Privacy-Preserving and Cross-Domain Human Sensing by Federated Domain Adaptation with Semantic Knowledge Correction. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 8:1. (1-26). Online publication date: 6-Mar-2024.

    https://doi.org/10.1145/3643503

  • Liu Q, Yan Y, Jin Y, Wang X, Ligeti P, Yu G and Yan X. (2024). Secure Federated Evolutionary Optimization—A Survey. Engineering. 10.1016/j.eng.2023.10.006. 34. (23-42). Online publication date: 1-Mar-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S2095809923004770

  • Wang P, Ouyang T, Wu Q, Huang Q, Gong J and Chen X. (2024). Hydra. Journal of Systems Architecture: the EUROMICRO Journal. 147:C. Online publication date: 1-Feb-2024.

    https://doi.org/10.1016/j.sysarc.2023.103052

  • Bochicchio M and Zeleke S. (2024). Personalized Federated Learning in Edge-Cloud Continuum for Privacy-Preserving Health Informatics: Opportunities and Challenges. Advanced Information Networking and Applications. 10.1007/978-3-031-57931-8_36. (368-378).

    https://link.springer.com/10.1007/978-3-031-57931-8_36

  • Park J, Lee K, Lee S, Zhang M and Ko J. (2023). AttFL. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 7:3. (1-31). Online publication date: 27-Sep-2023.

    https://doi.org/10.1145/3610917

  • Sandhu M, Prabhu D, Lu W, Kholghi M, Packer K, Higgins L, Varnfield M and Silvera-Tawil D. (2023). The Significance and Limitations of Sensor-based Agitation Detection in People Living with Dementia 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 10.1109/EMBC40787.2023.10340349. 979-8-3503-2447-1. (1-5).

    https://ieeexplore.ieee.org/document/10340349/

  • Psaltis A, Zafeirouli K, Leškovský P, Bourou S, Vásquez-Correa J, García-Pablos A, Cerezo Sánchez S, Dimou A, Patrikakis C and Daras P. (2023). Fostering Trustworthiness of Federated Learning Ecosystem through Realistic Scenarios. Information. 10.3390/info14060342. 14:6. (342).

    https://www.mdpi.com/2078-2489/14/6/342

  • Tashakori A, Zhang W, Jane Wang Z and Servati P. SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence. IEEE Internet of Things Journal. 10.1109/JIOT.2022.3233599. 10:10. (9161-9176).

    https://ieeexplore.ieee.org/document/10012038/

  • Dai J and Moffatt K. (2023). Enriching Social Sharing for the Dementia Community: Insights from In-Person and Online Social Programs. ACM Transactions on Accessible Computing. 16:1. (1-33). Online publication date: 31-Mar-2023.

    https://doi.org/10.1145/3582558

  • Ovi P, Gangopadhyay A, Erbacher R and Busart C. (2022). Secure Federated Training: Detecting Compromised Nodes and Identifying the Type of Attacks 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA). 10.1109/ICMLA55696.2022.00183. 978-1-6654-6283-9. (1115-1120).

    https://ieeexplore.ieee.org/document/10069230/