5 citations · 18 across the 19 of their papers we have counts for
19 papers
Differentially Private Ad Conversion Measurement
John Delaney, Badih Ghazi, Charlie Harrison +6
In this work, we study ad conversion measurement, a central functionality in digital advertising, where an advertiser seeks to estimate advertiser website (or mobile app) conversio…
Improved Lower Bound for Differentially Private Facility Location
Pasin Manurangsi
We consider the differentially private (DP) facility location problem in the so called super-set output setting proposed by Gupta et al. [SODA 2010]. The current best known expecte…
Training Differentially Private Ad Prediction Models with Semi-Sensitive Features
Lynn Chua, Qiliang Cui, Badih Ghazi +9
Motivated by problems arising in digital advertising, we introduce the task of training differentially private (DP) machine learning models with semi-sensitive features. In this se…
Sparsity-Preserving Differentially Private Training of Large Embedding Models
Badih Ghazi, Yangsibo Huang, Pritish Kamath +4
As the use of large embedding models in recommendation systems and language applications increases, concerns over user data privacy have also risen. DP-SGD, a training algorithm th…
User-Level Differential Privacy With Few Examples Per User
Badih Ghazi, Pritish Kamath, Ravi Kumar +3
Previous work on user-level differential privacy (DP) [Ghazi et al. NeurIPS 2021, Bun et al. STOC 2023] obtained generic algorithms that work for various learning tasks. However, t…
Hardness of Approximating Bounded-Degree Max 2-CSP and Independent Set on k-Claw-Free Graphs
Euiwoong Lee, Pasin Manurangsi
We consider the question of approximating Max 2-CSP where each variable appears in at most constraints (but with possibly arbitrarily large alphabet). There is a simple $(\frac…