Rasmus Pagh
Professor
Algorithms and Complexity
Universitetsparken 1
2100 København Ø
- 2024
- Published
Shannon meets Gray: Noise-robust, Low-sensitivity Codes with Applications in Differential Privacy
Lolck, David Rasmussen & Pagh, Rasmus, 2024, Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). SIAM, p. 1050-1066Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2023
- 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
- Published
Simple Set Sketching
Bæk Tejs Houen, J., 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. 228-241Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2022
- 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
- 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. 753-761Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 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
- 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
- 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
- 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
- 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. 83-90Research output: Contribution to journal › Journal article › Research › peer-review
ID: 252282120
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Efficient differentially private F0 linear sketching
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published