2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
Privacy by Postprocessing the Discrete Laplace Mechanism
Quentin Hillebrand, Jacob Imola, Rasmus Pagh +1
We show that an "old dog", the classical discrete Laplace (aka.~geometric) mechanism, can "perform new tricks": 1. It can be post-processed to yield a simple, unbiased estimator of…
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…
Facility Location Problem under Local Differential Privacy without Super-set Assumption
Kevin Pfisterer, Quentin Hillebrand, Vorapong Suppakitpaisarn
In this paper, we introduce an adaptation of the facility location problem and analyze it within the framework of local differential privacy (LDP). Under this model, we ensure the…
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…