Fully dynamic k-means coreset in near-optimal update time
M.D. La Tour, M. Henzinger, D. Saulpic, in:, 32nd Annual European Symposium on Algorithms, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024.

Data-efficient learning via clustering-based sensitivity sampling: Foundation models and beyond
K. Axiotis, V. Cohen-Addad, M. Henzinger, S. Jerome, V. Mirrokni, D. Saulpic, D.P. Woodruff, M. Wunder, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 2086–2107.

Experimental evaluation of fully dynamic k-means via coresets
M. Henzinger, D. Saulpic, L. Sidl, in:, 2024 Proceedings of the Symposium on Algorithm Engineering and Experiments, Society for Industrial and Applied Mathematics, 2024, pp. 220–233.

Making old things new: A unified algorithm for differentially private clustering
M.D. La Tour, M. Henzinger, D. Saulpic, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 12046–12086.

Deterministic clustering in high dimensional spaces: Sketches and approximation
V. Cohen-Addad, D. Saulpic, C. Schwiegelshohn, in:, 2023 IEEE 64th Annual Symposium on Foundations of Computer Science, IEEE, 2023, pp. 1105–1130.