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20132026
most citedScalable and Differentially Private Distributed Aggregation in the Shuffled Model

65 citations · 177 across the 68 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

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.DS2026

Fixed-Parameter Tractability of Private Synthetic Data Generation

Badih Ghazi, Cristóbal Guzmán, Pritish Kamath +3

We study the problem of generating synthetic data under differential privacy. We establish fixed-parameter tractability (FPT) for this problem where the parameter is the treewidth…

cs.DS2026

Convex Optimization with Local Label Differential Privacy: Tight Bounds in All Privacy Regimes

Lynn Chua, Badih Ghazi, Ravi Kumar +3

We study the problem of Stochastic Convex Optimization (SCO) under the constraint of local Label Differential Privacy (L-LDP). In this setting, the features are considered public,…

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.CG2026

Computational Hardness of Private Coreset

Badih Ghazi, Cristóbal Guzmán, Pritish Kamath +3

We study the problem of differentially private (DP) computation of coreset for the -means objective. For a given input set of points, a coreset is another set of points such tha…