Charlie Harrison

According to our database, Charlie Harrison authored at least 9 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Optimal Partition Selection with Rényi Differential Privacy.

Charlie Harrison, Pasin Manurangsi

Proceedings of the 7th Symposium on Foundations of Responsible Computing, 2026

Exact zCDP Characterizations for Fundamental Differentially Private Mechanisms.

Charlie Harrison, Pasin Manurangsi

Proceedings of the 7th Symposium on Foundations of Responsible Computing, 2026

2025

On the Differential Privacy and Interactivity of Privacy Sandbox Reports.

Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Mariana Raykova, Vikas Sahu, Phillipp Schoppmann

Proc. Priv. Enhancing Technol., 2025

Infinitely Divisible Noise for Differential Privacy: Nearly Optimal Error in the High ε Regime.

Charlie Harrison, Pasin Manurangsi

Proceedings of the 6th Symposium on Foundations of Responsible Computing, 2025

Balls-and-Bins Sampling for DP-SGD.

Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Differentially Private Ad Conversion Measurement.

John Delaney, Badih Ghazi, Charlie Harrison, Christina Ilvento, Ravi Kumar, Pasin Manurangsi, Martin Pál, Karthik Prabhakar, Mariana Raykova

Proc. Priv. Enhancing Technol., 2024

On the Differential Privacy and Interactivity of Privacy Sandbox Reports.

Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, S. Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Vikas Sahu

CoRR, 2024

Training Differentially Private Ad Prediction Models with Semi-Sensitive Features.

Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang

CoRR, 2024

Training Differentially Private Ad Prediction Models With Semi-Sensitive Features.

Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Nicolas Mayoraz, Hema Venkata Krishna Giri Narra, Steffen Rendle, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2024) co-located with the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), 2024