Cormode, Graham

16 publications

ICLRW 2025 Leveraging Vertical Public-Private Split for Improved Synthetic Data Generation Samuel Maddock, Shripad Gade, Graham Cormode, Will Bullock

NeurIPS 2025 Sum Estimation Under Personalized Local Differential Privacy Dajun Sun, Wei Dong, Yuan Qiu, Ke Yi, Graham Cormode

AISTATS 2024 Federated Experiment Design Under Distributed Differential Privacy Wei-Ning Chen, Graham Cormode, Akash Bharadwaj, Peter Romov, Ayfer Ozgur

ICMLW 2023 Federated Experiment Design Under Distributed Differential Privacy Wei-Ning Chen, Graham Cormode, Akash Bharadwaj, Peter Romov, Ayfer Ozgur

ICML 2023 Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting Jonathan Hehir, Daniel Ting, Graham Cormode

AISTATS 2023 The Communication Cost of Security and Privacy in Federated Frequency Estimation Wei-Ning Chen, Ayfer Ozgur, Graham Cormode, Akash Bharadwaj

AISTATS 2022 Sample-and-Threshold Differential Privacy: Histograms and Applications Graham Cormode, Akash Bharadwaj

ICLR 2022 On the Importance of Difficulty Calibration in Membership Inference Attacks Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles

NeurIPSW 2022 Reconciling Security and Communication Efficiency in Federated Learning Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock

AISTATS 2021 Sequential Random Sampling Revisited: Hidden Shuffle Method Michael Shekelyan, Graham Cormode

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

NeurIPSW 2021 Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour, Igor Shilov, Alexandre Sablayrolles, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Ghosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, Ilya Mironov

NeurIPSW 2021 Sample-and-Threshold Differential Privacy: Histograms and Applications Akash Bharadwaj, Graham Cormode

AISTATS 2018 Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams Chris Hickey, Graham Cormode

ICML 2018 Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms Charlie Dickens, Graham Cormode, David Woodruff

ICML 2015 Correlation Clustering in Data Streams KookJin Ahn, Graham Cormode, Sudipto Guha, Andrew McGregor, Anthony Wirth