Saulpic, David

8 publications

ICML 2025 Differentially Private Federated $k$-Means Clustering with Server-Side Data Jonathan Scott, Christoph H. Lampert, David Saulpic

ICML 2024 Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger, Sammy Jerome, Vahab Mirrokni, David Saulpic, David Woodruff, Michael Wunder

ICML 2024 Making Old Things New: A Unified Algorithm for Differentially Private Clustering Max Dupre La Tour, Monika Henzinger, David Saulpic

COLT 2022 Community Recovery in the Degree-Heterogeneous Stochastic Block Model Vincent Cohen-Addad, Frederik Mallmann-Trenn, David Saulpic

NeurIPS 2022 Improved Coresets for Euclidean $k$-Means Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn, Omar Ali Sheikh-Omar

NeurIPS 2021 Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn

NeurIPS 2020 On the Power of Louvain in the Stochastic Block Model Vincent Cohen-Addad, Adrian Kosowski, Frederik Mallmann-Trenn, David Saulpic

NeurIPS 2019 Fully Dynamic Consistent Facility Location Vincent Cohen-Addad, Niklas Oskar D Hjuler, Nikos Parotsidis, David Saulpic, Chris Schwiegelshohn