3 papers
cs.CR2026
LAPRAS : Learning-Augmented PRivate Answering for linear query Streams
Pranay Mundra, Adam Sealfon, Ziteng Sun +1
Modern database workloads are highly predictable: query streams are dominated by recurring jobs and templates, even when their arrival order is not known in advance. This motivates…
cs.LG2026
Denoising the US Census: Succinct Block Hierarchical Regression
Badih Ghazi, Pritish Kamath, Ravi Kumar +2
The US Census Bureau Disclosure Avoidance System (DAS) balances confidentiality and utility requirements for the decennial US Census (Abowd et al., 2022). The DAS was used in the 2…
cs.LG2025
Urania: Differentially Private Insights into AI Use
Daogao Liu, Edith Cohen, Badih Ghazi +8
We introduce , a novel framework for generating insights about LLM chatbot interactions with rigorous differential privacy (DP) guarantees. The framework employs a private…