Detecting and Anticipating Data Non-stationarity in Distributed Machine Learning

Project Details

Short titleDetecting and Anticipating Data Non-stationarity in Distributed Machine Learning
StatusFinished
Effective start/end date1/10/22 → 30/09/23

Funding

  • Royal Academy of Engineering

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  • 2 Conference contribution

  • An Impact Study of Concept Drift in Federated Learning

    Yang, G., Chen, X., Zhang, T., Wang, S. & Yang, Y., 5 Feb 2024, 2023 IEEE International Conference on Data Mining (ICDM). IEEE, p. 1457-1462 6 p. (IEEE International Conference on Data Mining (ICDM)).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    33 Downloads (Pure)

  • Triplets Oversampling for Class Imbalanced Federated Datasets

    Xiao, C. & Wang, S., 17 Sept 2023, Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part II. Koutra, D., Plant, C., Rodriguez, M. G., Baralis, E. & Bonchi, F. (eds.). 1 ed. Springer, p. 368–383 16 p. (Lecture Notes in Computer Science; vol. 14170).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    1 Downloads (Pure)