Rasmus Pagh

Rasmus Pagh

Professor


Publication year:
  1. Published

    A Smooth Binary Mechanism for Efficient Private Continual Observation

    Andersson, Joel Daniel & Pagh, Rasmus, 2023. 11 p.

    Research output: Contribution to conferencePaperResearch

  2. Published

    Fair near neighbor search via sampling

    Aumuller, M., Har-Peled, S., Mahabadi, S., Pagh, Rasmus & Silvestri, F., 2021, In: SIGMOD Record. 50, 1, p. 42-49

    Research output: Contribution to journalJournal articlepeer-review

  3. Published

    Sampling near neighbors in search for fairness

    Aumüller, M., Har-Peled, S., Mahabadi, S., Pagh, Rasmus & Silvestri, F., 2022, In: Communications of the ACM. 65, 8, p. 83-90

    Research output: Contribution to journalJournal articlepeer-review

  4. Published

    Sampling a Near Neighbor in High Dimensions-Who is the Fairest of Them All?

    Aumüller, M., Har-Peled, S., Mahabadi, S., Pagh, Rasmus & Silvestri, F., 2022, In: ACM Transactions on Database Systems. 47, 1, p. 1-40 4.

    Research output: Contribution to journalJournal articlepeer-review

  5. Published

    Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access

    Aumüller, M., Lebeda, C. J. & Pagh, Rasmus, 2022, In: Journal of Privacy and Confidentiality. 12, 2, 35 p.

    Research output: Contribution to journalJournal articlepeer-review

  6. Published

    Differentially Private Sparse Vectors with Low Error, Optimal Space, and Fast Access

    Aumüller, M., Lebeda, C. J. & Pagh, Rasmus, 2021, CCS 2021 - Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security. Association for Computing Machinery, p. 1223-1236 (Proceedings of the ACM Conference on Computer and Communications Security).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  7. Published

    Simple Set Sketching

    Houen, Jakob Bæk Tejs, Pagh, Rasmus & Walzer, S., 2023, Proceedings, 2023 Symposium on Simplicity in Algorithms (SOSA). Kavitha, T. & Mehlhorn, K. (eds.). Society for Industrial and Applied Mathematics, p. 228-241

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  8. Published

    On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy

    Ghazi, B., Golowich, N., Kumar, R., Pagh, Rasmus & Velingker, A., 2021, Advances in Cryptology – EUROCRYPT 2021 - 40th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. Canteaut, A. & Standaert, F-X. (eds.). Springer, p. 463-488 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12698 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  9. Published

    Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message

    Ghazi, B., Kumar, R., Manurangsi, P., Pagh, Rasmus & Sinha, A., 2021, Proceedings of the 38 th International Conference on Machine Learning. Meila, M. & Zhang, T. (eds.). PMLR, p. 3692-3701 (Proceedings of Machine Learning Research, Vol. 139).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  10. Advances and Open Problems in Federated Learning

    Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., D'Oliveira, R. G. L., Eichner, H., El Rouayheb, S., Evans, D., Gardner, J., Garrett, Z., Gascon, A., Ghazi, B., Gibbons, P. B., Gruteser, M. & 39 others, Harchaoui, Z., He, C., He, L., Huo, Z., Hutchinson, B., Hsu, J., Jaggi, M., Javidi, T., Joshi, G., Khodak, M., Konecny, J., Korolova, A., Koushanfar, F., Koyejo, S., Lepoint, T., Liu, Y., Mittal, P., Mohri, M., Nock, R., Ozgur, A., Pagh, Rasmus, Qi, H., Ramage, D., Raskar, R., Raykova, M., Song, D., Song, W., Stich, S. U., Sun, Z., Suresh, A. T., Tramer, F., Vepakomma, P., Wang, J., Xiong, L., Xu, Z., Yang, Q., Yu, F. X., Yu, H. & Zhao, S., 2021, In: Foundations and Trends in Machine Learning. 14, 1-2, p. 1-210

    Research output: Contribution to journalJournal articlepeer-review

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