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