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  • AGIC: Approximate Gradient Inversion Attack on Federated Learning

    Xu, J., Hong, C., Huang, J., Chen, L. Y. & Decouchant, J. E. A. P., 2023, 41st International Symposium on Reliable Distributed Systems (SRDS 2022 ). Ceballos, C. & Torres, H. (eds.). p. 12-22 11 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    File
    5 Citations (Scopus)
    53 Downloads (Pure)
  • Maverick Matters: Client Contribution and Selection in Federated Learning

    Huang, J., Hong, C., Liu, Y., Chen, L. Y. & Roos, S., 2023, Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Proceedings. Kashima, H., Ide, T. & Peng, W-C. (eds.). Springer, p. 269-282 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13936 LNCS).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    File
    2 Citations (Scopus)
    82 Downloads (Pure)
  • Online label aggregation: A variational bayesian approach

    Hong, C., Ghiassi, A., Zhou, Y., Birke, R. & Chen, L. Y., 2021, The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021. ACM, p. 1904-1915 (The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    File
    4 Citations (Scopus)
    120 Downloads (Pure)