237 citations · 312 across the 7 of their papers we have counts for
6 papers · 1 filter
Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs
Jieming Shi, Tianyuan Jin, Renchi Yang +2
Given a graph G and a node u in G, a single source SimRank query evaluates the similarity between u and every node v in G. Existing approaches to single source SimRank computation…
Collecting and Analyzing Data from Smart Device Users with Local Differential Privacy
Thông T. Nguyên, Xiaokui Xiao, Yin Yang +3
Organizations with a large user base, such as Samsung and Google, can potentially benefit from collecting and mining users' data. However, doing so raises privacy concerns, and ris…
Optimizing Batch Linear Queries under Exact and Approximate Differential Privacy
Ganzhao Yuan, Zhenjie Zhang, Marianne Winslett +3
Differential privacy is a promising privacy-preserving paradigm for statistical query processing over sensitive data. It works by injecting random noise into each query result, suc…
Low Rank Mechanism for Optimizing Batch Queries under Differential Privacy
Ganzhao Yuan, Zhenjie Zhang, Marianne Winslett +3
Differential privacy is a promising privacy-preserving paradigm for statistical query processing over sensitive data. It works by injecting random noise into each query result, suc…
Functional Mechanism: Regression Analysis under Differential Privacy
Jun Zhang, Zhenjie Zhang, Xiaokui Xiao +2
ε-differential privacy is the state-of-the-art model for releasing sensitive information while protecting privacy. Numerous methods have been proposed to enforce epsilon-differenti…
Low-Rank Mechanism: Optimizing Batch Queries under Differential Privacy
Ganzhao Yuan, Zhenjie Zhang, Marianne Winslett +3
Differential privacy is a promising privacy-preserving paradigm for statistical query processing over sensitive data. It works by injecting random noise into each query result, suc…