SAULPIC David : Algorithmes d'Approximation et Sketches Pour les Problèmes de Clustering.
Publications 2018-2024
2024
V. Cohen‑Addad, S. Gavva, C. Karthik, C. Mathieu, N. Namrata : “Fairness of linear regression in decision making”, International Journal of Data Science and Analytics, vol. 18 (3), pp. 337-347, (Springer Verlag) (2024)
V. Cohen‑Addad, A. Epasto, S. Lattanzi, V. Mirrokni, A. Munoz Medina, D. Saulpic, Ch. Schwiegelshohn, S. Vassilvitskii : “Scalable Differentially Private Clustering via Hierarchically Separated Trees”, KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington DC, United States, pp. 221-230, (ACM), (ISBN: 978-1-4503-9385-0) (2022)
V. Cohen‑Addad, K. Larsen, D. Saulpic, Ch. Schwiegelshohn : “Towards Optimal Lower Bounds for k-median and k-means Coresets”, Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2022, Rome, Italy, pp. 1038-1051, (Association for Computing Machinery), (ISBN: 9781450392648) (2022)
V. Cohen‑Addad, A. Gupta, L. Hu, H. Oh, D. Saulpic : “An Improved Local Search Algorithm for k-Median”, ACM-SIAM Symposium on Discrete Algorithms (SODA22), Alexandria (virtual event), VA, United States, pp. 1556-1612, (Society for Industrial and Applied Mathematics), (ISBN: 978-1-61197-707-3) (2022)
V. Cohen‑Addad, D. Saulpic, Ch. Schwiegelshohn : “A new coreset framework for clustering”, STOC 2021: Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing, Rome ( Virtual ), Italy, pp. 169-182, (ACM) (2021)
V. Cohen‑Addad, B. Guedj, V. Kanade, G. Rom : “Online $k$-means Clustering”, AISTATS 2021 - The 24th International Conference on Artificial Intelligence and Statistics, Virtual, France (2021)
2020
V. Cohen‑Addad, F. Mallmann‑Trenn, C. Mathieu : “Instance-Optimality in the Noisy Value-and Comparison-Model”, Proceedings of the 2020 {ACM-SIAM} Symposium on Discrete Algorithms, {SODA} 2020, Salt Lake City, United States, pp. 2124-2143, (Society for Industrial and Applied Mathematics) (2020)
2019
V. Cohen‑Addad, N. Hjuler, N. Parotsidis, D. Saulpic, Ch. Schwiegelshohn : “Fully Dynamic Consistent Facility Location”, NeurIPS'19 - 33rd Conference on Neural Information Processing Systems, Vancouver, United States (2019)
V. Cohen‑Addad, K. Srikanta : “Inapproximability of Clustering in Lp-metrics”, FOCS'19 - 60th Annual IEEE Symposium on Foundations of Computer Science, Baltimore, United States (2019)
V. Cohen‑Addad, V. Kanade, F. Mallmann‑Trenn, C. Mathieu : “Hierarchical Clustering”, Journal of the ACM (JACM), vol. 66 (4), pp. 1-42, (Association for Computing Machinery) (2019)
V. Cohen‑Addad, A. Gupta, A. Kumar, E. Lee, J. Li : “Tight FPT Approximations for k-Median and k-Means”, 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019), vol. 132, Leibniz International Proceedings in Informatics, Patras, Greece, pp. 42:1-42:14, (Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik) (2019)
V. Cohen‑Addad, J. Li : “On the Fixed-Parameter Tractability of Capacitated Clustering”, 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019), vol. 132, Leibniz International Proceedings in Informatics (LIPIcs), Patras, Greece, pp. 41:1-41:14, (Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik) (2019)
V. Cohen‑Addad, É. Colin de Verdière, D. Marx, A. De Mesmay : “Almost tight lower bounds for hard cutting problems in embedded graphs”, 35th International Symposium on Computational Geometry (SoCG 2019), vol. 129, Leibniz International Proceedings in Informatics (LIPIcs), Portland, OR, United States, pp. 27:1-27:16, (Schloss Dagstuhl -- Leibniz-Zentrum für Informatik) (2019)
M. Abrahamsen, A. Adamaszek, K. Bringmann, V. Cohen‑Addad, M. Mehr, E. Rotenberg, A. Roytman, M. Thorup : “Fast fencing”, The 50th Annual ACM SIGACT Symposium on Theory of Computing, Los Angeles, United States, pp. 564-573, (ACM Press) (2018)
V. Cohen‑Addad, A. De Mesmay, E. Rotenberg, A. Roytman : “The Bane of Low-Dimensionality Clustering”, Proceedings of the Twenty-Ninth ACM-SIAM Symposium on Discrete Algorithms, New Orleans, United States (2018)
V. Cohen‑Addad : “A Fast Approximation Scheme for Low-Dimensional k-Means”, SODA 2018 - 29h Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, LA, United States, pp. 430-440, (Society for Industrial and Applied Mathematics) (2018)
V. Cohen‑Addad, V. Kanade, F. Mallmann‑Trenn, C. Mathieu : “Hierarchical Clustering: Objective Functions and Algorithms”, SODA 2018 - Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, LA, United States, pp. 378-397, (Society for Industrial and Applied Mathematics) (2018)