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cs.IT2026
Refined Differentially Private Linear Regression via Extension of a Free Lunch Result
Sasmita Harini S, Anshoo Tandon
As data-privacy regulations tighten and statistical models are increasingly deployed on sensitive human-sourced data, privacy-preserving linear regression has become a critical nec…
cs.CR2026
On the Optimal Number of Grids for Differentially Private Non-Interactive -Means Clustering
Gokularam Muthukrishnan, Anshoo Tandon
Differentially private -means clustering enables releasing cluster centers derived from a dataset while protecting the privacy of the individuals. Non-interactive clustering tec…