Rasmus Pagh

Rasmus Pagh

Professor

ORCID: 0000-0002-1516-9306

Publication year:
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1 - 10 out of 16Page size: 10
  1. 2023
  2. Published

    A Smooth Binary Mechanism for Efficient Private Continual Observation

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

    Research output: Contribution to conference › Paper › Research

  3. 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 proceeding › Article in proceedings › Research › peer-review

  4. 2022
  5. Published

    DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search

    Karppa, M., Aumüller, M. & Pagh, Rasmus, 2022, Proceedings of the 25th International Conference on Artificial Intelligence and Statistics. PMLR, p. 3108-3137 (Proceedings of Machine Learning Research, Vol. 151).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  6. Published

    HyperLogLogLog: Cardinality Estimation With One Log More

    Karppa, M. & Pagh, Rasmus, 2022, KDD 2022 - Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, Inc., p. 753-761

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  7. Published

    Improved Utility Analysis of Private CountSketch

    Pagh, Rasmus & Thorup, Mikkel, 2022, Advances in Neural Information Processing Systems 35 (NeurIPS 2022). NeurIPS Proceedings, 13 p. (Advances in Neural Information Processing Systems, Vol. 35).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  8. Published

    Infinitely Divisible Noise in the Low Privacy Regime

    Pagh, Rasmus & Stausholm, N. M., 2022, Proceedings of The 33rd International Conference on Algorithmic Learning Theory. PMLR, p. 881-909 (Proceedings of Machine Learning Research, Vol. 167).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  9. 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 journal › Journal article › Research › peer-review

  10. 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 journal › Journal article › Research › peer-review

  11. 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 journal › Journal article › Research › peer-review

  12. 2021

  13. 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 journal › Journal article › Research › peer-review

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