2 citations · 2 across the 3 of their papers we have counts for
3 papers
Communication-Efficient Publication of Sparse Vectors under Differential Privacy
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
In this work, we propose a differentially private algorithm for publishing matrices aggregated from sparse vectors. These matrices include social network adjacency matrices, user-i…
Cycle Counting under Local Differential Privacy for Degeneracy-bounded Graphs
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
We propose an algorithm for counting the number of cycles under local differential privacy for degeneracy-bounded input graphs. Numerous studies have focused on counting the number…
Communication Cost Reduction for Subgraph Counting under Local Differential Privacy via Hash Functions
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
We suggest the use of hash functions to cut down the communication costs when counting subgraphs under edge local differential privacy. While various algorithms exist for computing…