2026
Improved Differentially Private Algorithms for Rank Aggregation
AAAI 2026technical
Rank aggregation is a task of combining the rankings of items from multiple users into a single ranking that best represents the users
3 accepted papers
Rank aggregation is a task of combining the rankings of items from multiple users into a single ranking that best represents the users
The problem of counting subgraphs or graphlets under local differential privacy is an important challenge that has attracted significant attention from researchers. However, much of the existing work focuses on small graphlets like triangles or $k$-stars. In this paper, we propose a non-interactive,…
In our study, we present an algorithm for publishing the count of walks and Katz centrality under local differential privacy (LDP), complemented by a comprehensive theoretical analysis. While previous research in LDP has predominantly focused on counting subgraphs with a maximum of five nodes, our w…