386 citations · 795 across the 50 of their papers we have counts for
13 papers · 1 filter
PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy
Kuntai Cai, Xiaokui Xiao, Graham Cormode
Answering database queries while preserving privacy is an important problem that has attracted considerable research attention in recent years. A canonical approach to this problem…
Weighted Random Sampling over Joins
Michael Shekelyan, Graham Cormode, Peter Triantafillou +2
Joining records with all other records that meet a linkage condition can result in an astronomically large number of combinations due to many-to-many relationships. For such challe…
Privacy-Preserving Synthetic Location Data in the Real World
Teddy Cunningham, Graham Cormode, Hakan Ferhatosmanoglu
Sharing sensitive data is vital in enabling many modern data analysis and machine learning tasks. However, current methods for data release are insufficiently accurate or granular…
Real-World Trajectory Sharing with Local Differential Privacy
Teddy Cunningham, Graham Cormode, Hakan Ferhatosmanoglu +1
Sharing trajectories is beneficial for many real-world applications, such as managing disease spread through contact tracing and tailoring public services to a population's travel…
Frequency Estimation under Local Differential Privacy [Experiments, Analysis and Benchmarks]
Graham Cormode, Samuel Maddock, Carsten Maple
Private collection of statistics from a large distributed population is an important problem, and has led to large scale deployments from several leading technology companies. The…
Answering Range Queries Under Local Differential Privacy
Tejas Kulkarni, Graham Cormode, Divesh Srivastava
Counting the fraction of a population having an input within a specified interval i.e. a \emph{range query}, is a fundamental data analysis primitive. Range queries can also be use…