1 citations · 1 across the 5 of their papers we have counts for
6 papers
On the Relationship Between Information-Theoretic Privacy Metrics And Probabilistic Information Privacy
Chong Xiao Wang, Wee Peng Tay
Information-theoretic (IT) measures based on -divergences have recently gained interest as a measure of privacy leakage as they allow for trading off privacy against utility usi…
Differentially Private Multi-Party Data Release for Linear Regression
Ruihan Wu, Xin Yang, Yuanshun Yao +4
Differentially Private (DP) data release is a promising technique to disseminate data without compromising the privacy of data subjects. However the majority of prior work has focu…
Semi-Nonparametric Estimation of Distribution Divergence in Non-Euclidean Spaces
Chong Xiao Wang, Wee Peng Tay
This paper explores methods for estimating or approximating the total variation distance and the chi-squared divergence of probability measures within topological sample spaces, us…
Data-driven Regularized Inference Privacy
Chong Xiao Wang, Wee Peng Tay
Data is used widely by service providers as input to inference systems to perform decision making for authorized tasks. The raw data however allows a service provider to infer othe…
Arbitrarily Strong Utility-Privacy Tradeoff in Multi-Agent Systems
Chong Xiao Wang, Yang Song, Wee Peng Tay
Each agent in a network makes a local observation that is linearly related to a set of public and private parameters. The agents send their observations to a fusion center to allow…
Compressive Privacy for a Linear Dynamical System
Yang Song, Chong Xiao Wang, Wee Peng Tay
We consider a linear dynamical system in which the state vector consists of both public and private states. One or more sensors make measurements of the state vector and sends info…