Xi He

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 41

Top Topics

Current Practices

Hypothesis Test

Differentially Private

Top Venues

Proc. VLDB Endow.

SIGMOD Conference

Proc. Priv. Enhancing Technol.

Publications

Xi He, Shufan Zhang
Differential Privacy with Fine-Grained Provenance: Opportunities and Challenges. IEEE Data Eng. Bull. 47 (2) (2024)
Shufan Zhang, Xi He, Ashish Kundu, Sharad Mehrotra, Shantanu Sharma
Secure Normal Form: Mediation Among Cross Cryptographic Leakages in Encrypted Databases. ICDE (2024)
Xi He
Technical Perspective: Synthetic Data Needs a Reproducibility Benchmark. SIGMOD Rec. 53 (1) (2024)
Shubhankar Mohapatra, Jianqiao Zong, Florian Kerschbaum, Xi He
Differentially Private Data Generation with Missing Data. Proc. VLDB Endow. 17 (8) (2024)
Nada Lahjouji, Sameera Ghayyur, Xi He, Sharad Mehrotra
ProBE: Proportioning Privacy Budget for Complex Exploratory Decision Support. CoRR (2024)
Shubhankar Mohapatra, Jianqiao Zong, Florian Kerschbaum, Xi He
Differentially Private Data Generation with Missing Data. CoRR (2023)
Shufan Zhang, Xi He
DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance. CoRR (2023)
Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman, Jennie Rogers
Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases. CoRR (2022)
Miti Mazmudar, Thomas Humphries, Jiaxiang Liu, Matthew Rafuse, Xi He
Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration. CoRR (2022)
Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, Om Thakkar
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection. AAAI (2022)
Miti Mazmudar, Thomas Humphries, Jiaxiang Liu, Matthew Rafuse, Xi He
Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration. Proc. VLDB Endow. 16 (4) (2022)
Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman, Jennie Rogers
Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases. Proc. Priv. Enhancing Technol. 2022 (2) (2022)
Jiaxiang Liu, Karl Knopf, Yiqing Tan, Bolin Ding, Xi He
Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration. Proc. VLDB Endow. 14 (12) (2021)
Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal
DP-cryptography: marrying differential privacy and cryptography in emerging applications. Commun. ACM 64 (2) (2021)
Xi He, Jennie Rogers, Johes Bater, Ashwin Machanavajjhala, Chenghong Wang, Xiao Wang
Practical Security and Privacy for Database Systems. SIGMOD Conference (2021)
Chang Ge, Shubhankar Mohapatra, Xi He, Ihab F. Ilyas
Kamino: Constraint-Aware Differentially Private Data Synthesis. Proc. VLDB Endow. 14 (10) (2021)
Helen H. Chen, Shubhankar Mohapatra, George Michalopoulos, Xi He, Ian McKillop
Federated Deep Learning Architecture for Personalized Healthcare. MIE (2021)
Siyuan Xia, Beizhen Chang, Karl Knopf, Yihan He, Yuchao Tao, Xi He
DPGraph: A Benchmark Platform for Differentially Private Graph Analysis. SIGMOD Conference (2021)
Christian Covington, Xi He, James Honaker, Gautam Kamath
Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential Privacy. CoRR (2021)
Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, Om Thakkar
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection. CoRR (2021)
Chang Ge, Shubhankar Mohapatra, Xi He, Ihab F. Ilyas
Kamino: Constraint-Aware Differentially Private Data Synthesis. CoRR (2020)
Yuchao Tao, Xi He, Ashwin Machanavajjhala, Sudeepa Roy
Computing Local Sensitivities of Counting Queries with Joins. CoRR (2020)
Johes Bater, Yongjoo Park, Xi He, Xiao Wang, Jennie Rogers
SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations. Proc. VLDB Endow. 13 (11) (2020)
Yuchao Tao, Xi He, Ashwin Machanavajjhala, Sudeepa Roy
Computing Local Sensitivities of Counting Queries with Joins. SIGMOD Conference (2020)
Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal
DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications. CoRR (2020)
Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha
Crypt?: Crypto-Assisted Differential Privacy on Untrusted Servers. SIGMOD Conference (2020)
Zhuolun Xiang, Bolin Ding, Xi He, Jingren Zhou
Linear and Range Counting under Metric-based Local Differential Privacy. ISIT (2020)
Ios Kotsogiannis, Yuchao Tao, Xi He, Maryam Fanaeepour, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
PrivateSQL: A Differentially Private SQL Query Engine. Proc. VLDB Endow. 12 (11) (2019)
Changchang Liu, Xi He, Thee Chanyaswad, Shiqiang Wang, Prateek Mittal
Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing. Proc. Priv. Enhancing Technol. 2019 (3) (2019)
Jennie Rogers, Johes Bater, Xi He, Ashwin Machanavajjhala, Madhav Suresh, Xiao Wang
Privacy Changes Everything. Poly/DMAH@VLDB (2019)
Chang Ge, Xi He, Ihab F. Ilyas, Ashwin Machanavajjhala
APEx: Accuracy-Aware Differentially Private Data Exploration. SIGMOD Conference (2019)
Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha
Outis: Crypto-Assisted Differential Privacy on Untrusted Servers. CoRR (2019)
Zhuolun Xiang, Bolin Ding, Xi He, Jingren Zhou
Design of Algorithms under Policy-Aware Local Differential Privacy: Utility-Privacy Trade-offs. CoRR (2019)
Johes Bater, Xi He, William Ehrich, Ashwin Machanavajjhala, Jennie Rogers
Shrinkwrap: Differentially-Private Query Processing in Private Data Federations. CoRR (2018)
Johes Bater, Xi He, William Ehrich, Ashwin Machanavajjhala, Jennie Rogers
ShrinkWrap: Efficient SQL Query Processing in Differentially Private Data Federations. Proc. VLDB Endow. 12 (3) (2018)
Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava
Composing Differential Privacy and Secure Computation: A Case Study on Scaling Private Record Linkage. CCS (2017)
Chang Ge, Ihab F. Ilyas, Xi He, Ashwin Machanavajjhala
Private Exploration Primitives for Data Cleaning. CoRR (2017)
Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava
Scaling Private Record Linkage using Output Constrained Differential Privacy. CoRR (2017)
Ashwin Machanavajjhala, Xi He, Michael Hay
Differential Privacy in the Wild: A Tutorial on Current Practices & Open Challenges. SIGMOD Conference (2017)
Ashwin Machanavajjhala, Xi He, Michael Hay
Differential Privacy in the Wild: A tutorial on current practices & open challenges. Proc. VLDB Endow. 9 (13) (2016)
Xi He, Nisarg Raval, Ashwin Machanavajjhala
A Demonstration of VisDPT: Visual Exploration of Differentially Private Trajectories. Proc. VLDB Endow. 9 (13) (2016)
Xi He, Graham Cormode, Ashwin Machanavajjhala, Cecilia M. Procopiuc, Divesh Srivastava
DPT: Differentially Private Trajectory Synthesis Using Hierarchical Reference Systems. Proc. VLDB Endow. 8 (11) (2015)
Xi He, Ashwin Machanavajjhala, Bolin Ding
Blowfish privacy: tuning privacy-utility trade-offs using policies. SIGMOD Conference (2014)
Xi He, Ashwin Machanavajjhala, Bolin Ding
Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies. CoRR (2013)