Skip to main navigation Skip to search Skip to main content
No photo of J. Huang

J. Huang

Fingerprint

Dive into the research topics where J. Huang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
  • 1 Similar Profiles

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
  • Detecting Vulnerabilities of Heterogeneous Federated Learning Systems

    Huang, J., 2026, 121 p.

    Research output: ThesisDissertation (TU Delft)

    Open Access
    File
    8 Downloads (Pure)
  • Single-Fold Distillation for Diffusion Models

    Hong, C., Huang, J., Birke, R., Epema, D., Roos, S. & Chen, L. Y., 2026, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Proceedings. Ribeiro, R. P., Jorge, A. M., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P. & Abreu, P. H. (eds.). Springer, p. 173-189 17 p. (Lecture Notes in Computer Science; vol. 16014 LNCS).

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

    Open Access
    File
    1 Downloads (Pure)
  • Adversarial Knowledge Extraction via Steering Diffusion Models

    Hong, C., Huang, J., Chen, L. & Birke, R., 2025, Neural Information Processing - 31st International Conference, ICONIP 2024, Proceedings. Mahmud, M., Doborjeh, M., Wong, K., Leung, A. C. S., Doborjeh, Z. & Tanveer, M. (eds.). Cham: Springer, p. 336-350 15 p. (Communications in Computer and Information Science; vol. 2293 CCIS).

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

    Open Access
    File
  • GIDM: Gradient Inversion of Federated Diffusion Models

    Huang, J., Hong, C., Roos, S. & Chen, L. Y., 2025, Availability, Reliability and Security - 20th International Conference, ARES 2025, Proceedings. Dalla Preda, M., Schrittwieser, S., Naessens, V. & De Sutter, B. (eds.). Cham: Springer, p. 380-401 22 p. (Lecture Notes in Computer Science; vol. 15992 LNCS).

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

    Open Access
    File
    1 Downloads (Pure)
  • TS-Inverse: A Gradient Inversion Attack Tailored for Federated Time Series Forecasting Models

    Meijer, C., Huang, J., Sharma, S., Lazovik, E. & Chen, L. Y., 2025, Proceedings - 2025 IEEE Conference on Secure and Trustworthy Machine Learning, SaTML 2025. New York, NY: IEEE, p. 110-124 15 p.

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

    Open Access
    File