activity
20232026
collaborators

8 papers

cs.LG2026

CALLIOPE: Private Insights into AI Use, Without Embeddings

Edith Cohen, Vadym Doroshenko, Badih Ghazi +11

We introduce CALLIOPE, a top-down framework for discovering topic hierarchies in large corpora of unstructured data (e.g., LLM conversations), while supporting differential privacy…

cs.DS2026

Online Differentially Private Consistent Clustering

Edith Cohen, Vadym Doroshenko, Badih Ghazi +7

We study differentially private (DP) -means and -median clustering in the online streaming setting. In this model, points arrive sequentially, and at each time step, we need…

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…

cs.DS2024

On Computing Pairwise Statistics with Local Differential Privacy

Badih Ghazi, Pritish Kamath, Ravi Kumar +2

We study the problem of computing pairwise statistics, i.e., ones of the form , where denotes the input to the th user, with…

cs.DS2024

Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization

Badih Ghazi, Pritish Kamath, Ravi Kumar +2

In this work, we give a new technique for analyzing individualized privacy accounting via the following simple observation: if an algorithm is one-sided add-DP, then its subsampled…

cs.CR2023

Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API

Hidayet Aksu, Badih Ghazi, Pritish Kamath +4

The Privacy Sandbox Attribution Reporting API has been recently deployed by Google Chrome to support the basic advertising functionality of attribution reporting (aka conversion me…