37 citations · 65 across the 4 of their papers we have counts for
3 papers · 1 filter
Measuring Database Unfairness via Dependency Quantification Under Differential Privacy
Mariia Vologdin, Yuchao Tao, Amir Gilad
Differential privacy (DP) has become the de facto standard for protecting sensitive data, providing strong guarantees that published statistics or models reveal limited information…
DPXPlain: Privately Explaining Aggregate Query Answers
Yuchao Tao, Amir Gilad, Ashwin Machanavajjhala +1
Differential privacy (DP) is the state-of-the-art and rigorous notion of privacy for answering aggregate database queries while preserving the privacy of sensitive information in t…
Computing Local Sensitivities of Counting Queries with Joins
Yuchao Tao, Xi He, Ashwin Machanavajjhala +1
Local sensitivity of a query Q given a database instance D, i.e. how much the output Q(D) changes when a tuple is added to D or deleted from D, has many applications including quer…