7 papers
Near-Optimal Generalized Private Testing
Anamay Chaturvedi, Monika Henzinger, Jalaj Upadhyay
In differential privacy (DP), the generalized private testing problem was introduced by Liu and Talwar (STOC 2019). Given a dataset and a sequence of black-box…
Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting
Monika Henzinger, Nikita P. Kalinin, Jalaj Upadhyay
The factorization norms of the lower-triangular all-ones matrix, and , play a central role in differential privacy as they are use…
Correlated Noise Mechanisms for Differentially Private Learning
Krishna Pillutla, Jalaj Upadhyay, Christopher A. Choquette-Choo +9
This monograph explores the design and analysis of correlated noise mechanisms for differential privacy (DP), focusing on their application to private training of AI and machine le…
Binned Group Algebra Factorization for Differentially Private Continual Counting
Monika Henzinger, Nikita P. Kalinin, Jalaj Upadhyay
We study memory-efficient matrix factorization for differentially private counting under continual observation. While recent work by Henzinger and Upadhyay 2024 introduced a factor…
Improved Differentially Private Continual Observation Using Group Algebra
Monika Henzinger, Jalaj Upadhyay
Differentially private weighted prefix sum under continual observation is a crucial component in the production-level deployment of private next-word prediction for Gboard, which,…
Continual Counting with Gradual Privacy Expiration
Joel Daniel Andersson, Monika Henzinger, Rasmus Pagh +2
Differential privacy with gradual expiration models the setting where data items arrive in a stream and at a given time the privacy loss guaranteed for a data item seen at time…