David Saulpic
5 Publications
2024 | Published | Conference Paper | IST-REx-ID: 18308 | 
La Tour MD, Henzinger M, Saulpic D. Fully dynamic k-means coreset in near-optimal update time. In: 32nd Annual European Symposium on Algorithms. Vol 308. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2024. doi:10.4230/LIPIcs.ESA.2024.100
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2024 | Published | Conference Paper | IST-REx-ID: 18115 |
Axiotis K, Cohen-Addad V, Henzinger M, et al. Data-efficient learning via clustering-based sensitivity sampling: Foundation models and beyond. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:2086-2107.
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2024 | Published | Conference Paper | IST-REx-ID: 14769 |
Henzinger M, Saulpic D, Sidl L. Experimental evaluation of fully dynamic k-means via coresets. In: 2024 Proceedings of the Symposium on Algorithm Engineering and Experiments. Society for Industrial and Applied Mathematics; 2024:220-233. doi:10.1137/1.9781611977929.17
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2024 | Published | Conference Paper | IST-REx-ID: 18116 |
La Tour MD, Henzinger M, Saulpic D. Making old things new: A unified algorithm for differentially private clustering. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:12046-12086.
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2023 | Published | Conference Paper | IST-REx-ID: 14768 |
Cohen-Addad V, Saulpic D, Schwiegelshohn C. Deterministic clustering in high dimensional spaces: Sketches and approximation. In: 2023 IEEE 64th Annual Symposium on Foundations of Computer Science. IEEE; 2023:1105-1130. doi:10.1109/focs57990.2023.00066
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5 Publications
2024 | Published | Conference Paper | IST-REx-ID: 18308 |
La Tour MD, Henzinger M, Saulpic D. Fully dynamic k-means coreset in near-optimal update time. In: 32nd Annual European Symposium on Algorithms. Vol 308. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2024. doi:10.4230/LIPIcs.ESA.2024.100
[Published Version]
View
| Files available
| DOI
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18115 |
Axiotis K, Cohen-Addad V, Henzinger M, et al. Data-efficient learning via clustering-based sensitivity sampling: Foundation models and beyond. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:2086-2107.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 14769 |
Henzinger M, Saulpic D, Sidl L. Experimental evaluation of fully dynamic k-means via coresets. In: 2024 Proceedings of the Symposium on Algorithm Engineering and Experiments. Society for Industrial and Applied Mathematics; 2024:220-233. doi:10.1137/1.9781611977929.17
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18116 |
La Tour MD, Henzinger M, Saulpic D. Making old things new: A unified algorithm for differentially private clustering. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:12046-12086.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14768 |
Cohen-Addad V, Saulpic D, Schwiegelshohn C. Deterministic clustering in high dimensional spaces: Sketches and approximation. In: 2023 IEEE 64th Annual Symposium on Foundations of Computer Science. IEEE; 2023:1105-1130. doi:10.1109/focs57990.2023.00066
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv