Pagh, Rasmus

15 publications

NeurIPS 2025 Differentially Private Quantiles with Smaller Error Jacob Imola, Fabrizio Boninsegna, Hannah Keller, Anders Aamand, Amrita Roy Chowdhury, Rasmus Pagh

ICML 2025 Lightweight Protocols for Distributed Private Quantile Estimation Anders Aamand, Fabrizio Boninsegna, Abigail Gentle, Jacob Imola, Rasmus Pagh

ICML 2025 Private Lossless Multiple Release Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson, Rasmus Pagh

NeurIPS 2024 Continual Counting with Gradual Privacy Expiration Joel Daniel Andersson, Monika Henzinger, Rasmus Pagh, Teresa Anna Steiner, Jalaj Upadhyay

ICML 2024 Profile Reconstruction from Private Sketches Hao Wu, Rasmus Pagh

NeurIPS 2023 A Smooth Binary Mechanism for Efficient Private Continual Observation Joel Daniel Andersson, Rasmus Pagh

AISTATS 2022 DEANN: Speeding up Kernel-Density Estimation Using Approximate Nearest Neighbor Search Matti Karppa, Martin Aumüller, Rasmus Pagh

NeurIPS 2022 Improved Utility Analysis of Private CountSketch Rasmus Pagh, Mikkel Thorup

ALT 2022 Infinitely Divisible Noise in the Low Privacy Regime Rasmus Pagh, Nina Mesing Stausholm

FnTML 2021 Advances and Open Problems in Federated Learning Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao

ICML 2021 CountSketches, Feature Hashing and the Median of Three Kasper Green Larsen, Rasmus Pagh, Jakub Tětek

ICML 2021 Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha

ICML 2020 Composable Sketches for Functions of Frequencies: Beyond the Worst Case Edith Cohen, Ofir Geri, Rasmus Pagh

ICML 2020 Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh

NeurIPS 2020 WOR and $p$'s: Sketches for $\ell_p$-Sampling Without Replacement Edith Cohen, Rasmus Pagh, David Woodruff