activity
20192021
most citedPCKV: Locally Differentially Private Correlated Key-Value Data Collection with Optimized Utility

17 citations · 23 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2021

An Analysis Of Protected Health Information Leakage In Deep-Learning Based De-Identification Algorithms

Salman Seyedi, Li Xiong, Shamim Nemati +1

The increasing complexity of algorithms for analyzing medical data, including de-identification tasks, raises the possibility that complex algorithms are learning not just the gene…

cs.LG2020

Spatio-Temporal Tensor Sketching via Adaptive Sampling

Jing Ma, Qiuchen Zhang, Joyce C. Ho +1

Mining massive spatio-temporal data can help a variety of real-world applications such as city capacity planning, event management, and social network analysis. The tensor represen…

cs.CR20203 cited

PGLP: Customizable and Rigorous Location Privacy through Policy Graph

Yang Cao, Yonghui Xiao, Shun Takagi +6

Location privacy has been extensively studied in the literature. However, existing location privacy models are either not rigorous or not customizable, which limits the trade-off b…

cs.CR201917 cited

PCKV: Locally Differentially Private Correlated Key-Value Data Collection with Optimized Utility

Xiaolan Gu, Ming Li, Yueqiang Cheng +2

Data collection under local differential privacy (LDP) has been mostly studied for homogeneous data. Real-world applications often involve a mixture of different data types such as…

cs.CR20193 cited

Providing Input-Discriminative Protection for Local Differential Privacy

Xiaolan Gu, Ming Li, Li Xiong +1

Local Differential Privacy (LDP) provides provable privacy protection for data collection without the assumption of the trusted data server. In the real-world scenario, different d…

cs.LG2019

Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis

Jing Ma, Qiuchen Zhang, Jian Lou +3

Tensor factorization has been demonstrated as an efficient approach for computational phenotyping, where massive electronic health records (EHRs) are converted to concise and meani…