25 citations · 43 across the 10 of their papers we have counts for
3 papers · 1 filter
Differential Privacy from Locally Adjustable Graph Algorithms: -Core Decomposition, Low Out-Degree Ordering, and Densest Subgraphs
Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova +3
Differentially private algorithms allow large-scale data analytics while preserving user privacy. Designing such algorithms for graph data is gaining importance with the growth of…
Differentially Private Sampling from Distributions
Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith +1
We initiate an investigation of private sampling from distributions. Given a dataset with independent observations from an unknown distribution , a sampling algorithm must o…
The Price of Differential Privacy under Continual Observation
Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar +1
We study the accuracy of differentially private mechanisms in the continual release model. A continual release mechanism receives a sensitive dataset as a stream of inputs and…