David Saulpic - RankMe

53 papers A* 17A 6Journal 27Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Almost-Optimal Upper and Lower Bounds for Clustering in Low Dimensional Euclidean Spaces. CoRR Vincent Cohen-Addad, Karthik C. S., David Saulpic, Chris Schwiegelshohn
2026	J	`jnl`	Near-Optimal Bounds for Parameterized Euclidean k-means. CoRR Vincent Cohen-Addad, Karthik C. S., David Saulpic, Chris Schwiegelshohn
2025	A*	`conf`	A Tight VC-Dimension Analysis of Clustering Coresets with Applications. SODA Vincent Cohen-Addad, Andrew Draganov, Matteo Russo, David Saulpic, Chris Schwiegelshohn
2025	J	`jnl`	A Tight VC-Dimension Analysis of Clustering Coresets with Applications. CoRR Vincent Cohen-Addad, Andrew Draganov, Matteo Russo, David Saulpic, Chris Schwiegelshohn
2025	J	`jnl`	Differentially Private Federated CoRR Jonathan Scott, Christoph H. Lampert, David Saulpic
2025	A*	`conf`	Differentially Private Federated k-Means Clustering with Server-Side Data. ICML Jonathan Scott, Christoph H. Lampert, David Saulpic
2025	—	`conf`	Estimating the Electoral Consequences of Legislative Redistricting in France. FAccT Evripidis Bampis, Thomas Ehrhard, Bruno Escoffier, Claire Mathieu, Fanny Pascual, David Saulpic
2025	J	`jnl`	Improved Lower Bounds for Privacy under Continual Release. CoRR Bardiya Aryanfard, Monika Henzinger, David Saulpic, A. R. Sricharan
2024	J	`jnl`	Almost-linear Time Approximation Algorithm to Euclidean k-median and k-means. CoRR Max Dupré la Tour, David Saulpic
2024	A*	`conf`	Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond. ICML Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger, Sammy Jerome, Vahab Mirrokni, David Saulpic, David P. Woodruff, Michael Wunder
2024	J	`jnl`	Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond. CoRR Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger, Sammy Jerome, Vahab Mirrokni, David Saulpic, David P. Woodruff, Michael Wunder
2024	A	`conf`	Experimental Evaluation of Fully Dynamic ALENEX Monika Henzinger, David Saulpic, Leonhard Sidl
2024	A	`conf`	Fully Dynamic k-Means Coreset in Near-Optimal Update Time. ESA Max Dupré la Tour, Monika Henzinger, David Saulpic
2024	J	`jnl`	Fully Dynamic k-Means Coreset in Near-Optimal Update Time. CoRR Max Dupré la Tour, Monika Henzinger, David Saulpic
2024	A*	`conf`	Making Old Things New: A Unified Algorithm for Differentially Private Clustering. ICML Max Dupré la Tour, Monika Henzinger, David Saulpic
2024	J	`jnl`	Making Old Things New: A Unified Algorithm for Differentially Private Clustering. CoRR Max Dupré la Tour, Monika Henzinger, David Saulpic
2024	A*	`conf`	Sensitivity Sampling for k-Means: Worst Case and Stability Optimal Coreset Bounds. FOCS Nikhil Bansal, Vincent Cohen-Addad, Milind Prabhu, David Saulpic, Chris Schwiegelshohn
2024	J	`jnl`	Sensitivity Sampling for k-Means: Worst Case and Stability Optimal Coreset Bounds. CoRR Nikhil Bansal, Vincent Cohen-Addad, Milind Prabhu, David Saulpic, Chris Schwiegelshohn
2024	J	`jnl`	Settling Time vs. Accuracy Tradeoffs for Clustering Big Data. CoRR Andrew Draganov, David Saulpic, Chris Schwiegelshohn
2024	J	`jnl`	Settling Time vs. Accuracy Tradeoffs for Clustering Big Data. Proc. ACM Manag. Data Andrew Draganov, David Saulpic, Chris Schwiegelshohn
2023	A*	`conf`	Deterministic Clustering in High Dimensional Spaces: Sketches and Approximation. FOCS Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn
2023	J	`jnl`	Deterministic Clustering in High Dimensional Spaces: Sketches and Approximation. CoRR Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn
2023	J	`jnl`	Differential Privacy for Clustering Under Continual Observation. CoRR Max Dupré la Tour, Monika Henzinger, David Saulpic
2023	J	`jnl`	Experimental Evaluation of Fully Dynamic k-Means via Coresets. CoRR Monika Henzinger, David Saulpic, Leonhard Sidl
2022	A*	`conf`	A Massively Parallel Modularity-Maximizing Algorithm with Provable Guarantees. PODC Vincent Cohen-Addad, Frederik Mallmann-Trenn, David Saulpic
2022	A*	`conf`	An Improved Local Search Algorithm for k-Median. SODA Vincent Cohen-Addad, Anupam Gupta, Lunjia Hu, Hoon Oh, David Saulpic
2022	—	`—`	Approximation Algorithms and Sketches for Clustering. (Algorithmes d'approximation et sketches pour les problèmes de clustering). David Saulpic
2022	A*	`conf`	Community Recovery in the Degree-Heterogeneous Stochastic Block Model. COLT Vincent Cohen-Addad, Frederik Mallmann-Trenn, David Saulpic
2022	A*	`conf`	Improved Coresets for Euclidean k-Means. NeurIPS Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn, Omar Ali Sheikh-Omar
2022	J	`jnl`	Improved Coresets for Euclidean k-Means. CoRR Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn, Omar Ali Sheikh-Omar
2022	A*	`conf`	Scalable Differentially Private Clustering via Hierarchically Separated Trees. KDD Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
2022	J	`jnl`	Scalable Differentially Private Clustering via Hierarchically Separated Trees. CoRR Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
2022	J	`jnl`	Towards Optimal Lower Bounds for k-median and k-means Coresets. CoRR Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn
2022	A*	`conf`	Towards optimal lower bounds for k-median and k-means coresets. STOC Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn
2021	J	`jnl`	A New Coreset Framework for Clustering. CoRR Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn
2021	A*	`conf`	A new coreset framework for clustering. STOC Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn
2021	J	`jnl`	An Improved Local Search Algorithm for k-Median. CoRR Vincent Cohen-Addad, Anupam Gupta, Lunjia Hu, Hoon Oh, David Saulpic
2021	A*	`conf`	Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces. NeurIPS Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn
2021	J	`jnl`	Near-linear Time Approximation Schemes for Clustering in Doubling Metrics. J. ACM Vincent Cohen-Addad, Andreas Emil Feldmann, David Saulpic
2021	J	`jnl`	Polynomial time approximation schemes for clustering in low highway dimension graphs. J. Comput. Syst. Sci. Andreas Emil Feldmann, David Saulpic
2020	A*	`conf`	On the Power of Louvain in the Stochastic Block Model. NeurIPS Vincent Cohen-Addad, Adrian Kosowski, Frederik Mallmann-Trenn, David Saulpic
2020	A	`conf`	Polynomial Time Approximation Schemes for Clustering in Low Highway Dimension Graphs. ESA Andreas Emil Feldmann, David Saulpic
2020	J	`jnl`	Polynomial Time Approximation Schemes for Clustering in Low Highway Dimension Graphs. CoRR Andreas Emil Feldmann, David Saulpic
2019	A	`conf`	Dominating Sets and Connected Dominating Sets in Dynamic Graphs. STACS Niklas Hjuler, Giuseppe F. Italiano, Nikos Parotsidis, David Saulpic
2019	J	`jnl`	Dominating Sets and Connected Dominating Sets in Dynamic Graphs. CoRR Niklas Hjuler, Giuseppe F. Italiano, Nikos Parotsidis, David Saulpic
2019	A*	`conf`	Fully Dynamic Consistent Facility Location. NeurIPS Vincent Cohen-Addad, Niklas Hjuler, Nikos Parotsidis, David Saulpic, Chris Schwiegelshohn
2019	A*	`conf`	Near-Linear Time Approximations Schemes for Clustering in Doubling Metrics. FOCS David Saulpic, Vincent Cohen-Addad, Andreas Emil Feldmann
2018	J	`jnl`	Near-Linear Time Approximation Schemes for Clustering in Doubling Metrics. CoRR Vincent Cohen-Addad, Andreas Emil Feldmann, David Saulpic
2018	A	`conf`	Polynomial-Time Approximation Schemes for k-center, k-median, and Capacitated Vehicle Routing in Bounded Highway Dimension. ESA Amariah Becker, Philip N. Klein, David Saulpic
2017	A	`conf`	A Quasi-Polynomial-Time Approximation Scheme for Vehicle Routing on Planar and Bounded-Genus Graphs. ESA Amariah Becker, Philip N. Klein, David Saulpic
2017	J	`jnl`	Generating Functionally Equivalent Programs Having Non-Isomorphic Control-Flow Graphs. CoRR Rémi Géraud, Mirko Koscina, Paul Lenczner, David Naccache, David Saulpic
2017	—	`conf`	Generating Functionally Equivalent Programs Having Non-isomorphic Control-Flow Graphs. NordSec Rémi Géraud, Mirko Koscina, Paul Lenczner, David Naccache, David Saulpic
2017	J	`jnl`	Polynomial-Time Approximation Schemes for k-Center and Bounded-Capacity Vehicle Routing in Metrics with Bounded Highway Dimension. CoRR Amariah Becker, Philip N. Klein, David Saulpic