3 papers
cs.CR2026
Fast and Private Max-Sum Diversification
Ron Zadicario, Tova Milo
Result diversification is crucial for generating informative, non-redundant data summaries and query outputs. Although its various formulations have been extensively studied across…
cs.DS2026
Differentially Private Submodular Maximization with a Knapsack Constraint
Ron Zadicario, Tova Milo
Submodular maximization subject to a knapsack constraint (SMK) is a fundamental problem in discrete optimization, with wide-ranging applications in machine learning and related fie…
cs.CR2025
Differentially Private Explanations for Clusters
Amir Gilad, Tova Milo, Kathy Razmadze +1
The dire need to protect sensitive data has led to various flavors of privacy definitions. Among these, Differential privacy (DP) is considered one of the most rigorous and secure…