Publicações 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)
• 2023
  • M. Darrin, A. Samudre, M. Sahun, S. Atwell, C. Badens, A. Charrier, E. Helfer, A. Viallat, V. Cohen‑Addad, S. Giffard‑Roisin : “Classification of red cell dynamics with convolutional and recurrent neural networks: a sickle cell disease case study”, Scientific Reports, vol. 13 (1), pp. 745, (Nature Publishing Group) (2023)
• 2022
  • Th. Ehrhard, S. Attias, E. Bampis, V. Cohen‑Addad, B. Escoffier, C. Mathieu, F. Pascual, A. Pass‑Lanneau, D. Saulpic : “Découpage électoral des circonscriptions législatives en France: déséquilibres démographiques et contraintes territoriales”, Revue Française de Science Politique, vol. Vol. 72 (3), pp. 333-364, (Presses de Sciences Po) (2022)
  • 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 28^th 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, F. Mallmann‑Trenn, D. Saulpic : “A Massively Parallel Modularity-Maximizing Algorithm with Provable Guarantees”, PODC'22: Proceedings of the 2022 ACM Symposium on Principles of Distributed Computing, Salerno, Italy, pp. 356-365, (ACM) (2022)
  • V. Cohen‑Addad, F. Mallmann‑Trenn, D. Saulpic : “Community Recovery in the Degree-Heterogeneous Stochastic Block Model”, Proceedings of Machine Learning Research, vol. 178, Londres, United Kingdom, pp. 1662-1692, (PMLR) (2022)
  • V. Cohen‑Addad, K. Larsen, D. Saulpic, Ch. Schwiegelshohn : “Towards Optimal Lower Bounds for k-median and k-means Coresets”, Proceedings of the 54^th 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)
• 2021
  • V. Cohen‑Addad, A. Feldmann, D. Saulpic : “Near-linear Time Approximation Schemes for Clustering in Doubling Metrics”, Journal of the ACM (JACM), vol. 68 (6), pp. 1-34, (Association for Computing Machinery) (2021)
  • S. Mauras, V. Cohen‑Addad, G. Duboc, M. Dupré la Tour, P. Frasca, C. Mathieu, L. Opatowski, L. Viennot : “Mitigating COVID-19 outbreaks in workplaces and schools by hybrid telecommuting”, PLoS Computational Biology, vol. 17 (8), pp. 1-24, (PLOS) (2021)
  • V. Cohen‑Addad, É. Colin de Verdière, D. Marx, A. De Mesmay : “Almost tight lower bounds for hard cutting problems in embedded graphs”, Journal of the ACM (JACM), vol. 68 (30), pp. 1-26, (Association for Computing Machinery) (2021)
  • V. Cohen‑Addad, D. Saulpic, Ch. Schwiegelshohn : “A new coreset framework for clustering”, STOC 2021: Proceedings of the 53^rd Annual ACM SIGACT Symposium on Theory of Computing, Rome ( Virtual ), Italy, pp. 169-182, (ACM) (2021)
  • V. Cohen‑Addad, É. Colin de Verdière, A. De Mesmay : “A Near-Linear Approximation Scheme for Multicuts of Embedded Graphs with a Fixed Number of Terminals”, SIAM Journal on Computing, vol. 50 (1), pp. 1-31, (Society for Industrial and Applied Mathematics) (2021)
  • V. Cohen‑Addad, D. Saulpic, Ch. Schwiegelshohn : “Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces”, Advances in Neural Information Processing Systems, vol. 34, Virtual, France, pp. 21085-21098, (Curran Associates, Inc.), (ISBN: 9781713845393) (2021)
  • V. Cohen‑Addad, B. Guedj, V. Kanade, G. Rom : “Online $k$-means Clustering”, AISTATS 2021 - The 24^th 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 - 33^rd Conference on Neural Information Processing Systems, Vancouver, United States (2019)
  • A. Abboud, V. Cohen‑Addad, H. Houdrougé : “Subquadratic High-Dimensional Hierarchical Clustering”, NeurIPS'19 - 33^rd Conference on Neural Information Processing Systems, Vancouver, Canada (2019)
  • V. Cohen‑Addad, M. Pilipczuk, M. Pilipczuk : “A Polynomial-Time Approximation Scheme for Facility Location on Planar Graphs”, FOCS'19, Baltimore, United States (2019)
  • V. Cohen‑Addad, K. Srikanta : “Inapproximability of Clustering in Lp-metrics”, FOCS'19 - 60^th Annual IEEE Symposium on Foundations of Computer Science, Baltimore, United States (2019)
  • V. Cohen‑Addad, A. Feldmann, D. Saulpic : “Near-linear time approximations schemes for clustering in doubling metrics”, FOCS'19, 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”, 46^th 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)
  • L. Becchetti, M. Bury, V. Cohen‑Addad, F. Grandoni, Ch. Schwiegelshohn : “Oblivious dimension reduction for k -means: beyond subspaces and the Johnson-Lindenstrauss lemma”, STOC 2019 - 51^st Annual ACM SIGACT Symposium on Theory of Computing, Phoenix, United States, pp. 1039-1050, (ACM Press) (2019)
  • V. Cohen‑Addad, Ph. Klein, C. Mathieu : “Local Search Yields Approximation Schemes for $k$-Means and $k$-Median in Euclidean and Minor-Free Metrics”, SIAM Journal on Computing, vol. 48 (2), pp. 644-667, (Society for Industrial and Applied Mathematics) (2019)
  • V. Cohen‑Addad, L. Feuilloley, T. Starikovskaya : “Lower bounds for text indexing with mismatches and differences”, SODA 2019 - Symposium on Discrete Algorithms, San Diego, United States (2019)
  • V. Cohen‑Addad, J. Li : “On the Fixed-Parameter Tractability of Capacitated Clustering”, 46^th 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, M. Pilipczuk, M. Pilipczuk : “Efficient Approximation Schemes for Uniform-Cost Clustering Problems in Planar Graphs”, European Symposium on Algorithms, vol. 144, Leibniz International Proceedings in Informatics (LIPIcs), Munich, Germany, pp. 33:1-33:14, (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”, 35^th 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)
• 2018
  • V. Cohen‑Addad, Ph. Klein, N. Young : “Balanced centroidal power diagrams for redistricting”, The 26^th ACM SIGSPATIAL International Conference, Seattle, United States, pp. 389-396, (ACM Press) (2018)
  • M. Abrahamsen, A. Adamaszek, K. Bringmann, V. Cohen‑Addad, M. Mehr, E. Rotenberg, A. Roytman, M. Thorup : “Fast fencing”, The 50^th Annual ACM SIGACT Symposium on Theory of Computing, Los Angeles, United States, pp. 564-573, (ACM Press) (2018)
  • V. Cohen‑Addad, É. Colin de Verdière, A. De Mesmay : “A Near-Linear Approximation Scheme for Multicuts of Embedded Graphs with a Fixed Number of Terminals”, Proceedings of the Twenty-Ninth ACM-SIAM Symposium on Discrete Algorithms, New Orleans, United States, pp. 1439-1458 (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)