Field-Based Coordination for Federated Learning

Author:

Domini DavideORCID,Aguzzi GianlucaORCID,Esterle LukasORCID,Viroli MirkoORCID

Publisher

Springer Nature Switzerland

Reference40 articles.

1. Aguzzi, G.: Research directions for aggregate computing with machine learning. In: El-Araby, E., et al. (eds.) IEEE International Conference on Autonomic Computing and Self-organizing Systems, ACSOS 2021, Companion Volume, Washington, DC, USA, 27 September–1 Octoter 2021, pp. 310–312. IEEE (2021). https://doi.org/10.1109/ACSOS-C52956.2021.00078

2. Aguzzi, G., Casadei, R., Pianini, D., Viroli, M.: Dynamic decentralization domains for the internet of things. IEEE Internet Comput. 26(6), 16–23 (2022). https://doi.org/10.1109/MIC.2022.3216753

3. Aguzzi, G., Casadei, R., Viroli, M.: Addressing collective computations efficiency: towards a platform-level reinforcement learning approach. In: Casadei, R., et al. (eds.) IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2022, Virtual, CA, USA, 19–23 September 2022, pp. 11–20. IEEE (2022). https://doi.org/10.1109/ACSOS55765.2022.00019

4. Aguzzi, G., Casadei, R., Viroli, M.: Machine learning for aggregate computing: a research roadmap. In: 42nd IEEE International Conference on Distributed Computing Systems, ICDCS Workshops, Bologna, Italy, 10 July 2022, pp. 119–124. IEEE (2022). https://doi.org/10.1109/ICDCSW56584.2022.00032

5. Aguzzi, G., Casadei, R., Viroli, M.: Towards reinforcement learning-based aggregate computing. In: ter Beek, M.H., Sirjani, M. (eds.) COORDINATION 2022. IFIP Advances in Information and Communication Technology, vol. 13271, pp. 72–91. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-08143-9_5

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