Xi He

According to our database, Xi He authored at least 41 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Preventing Inferences Through Data Dependencies on Sensitive Data.

Primal Pappachan, Shufan Zhang, Xi He, Sharad Mehrotra

IEEE Trans. Knowl. Data Eng., October, 2024

Differentially Private Data Generation with Missing Data.

Shubhankar Mohapatra, Jianqiao Zong, Florian Kerschbaum, Xi He

Proc. VLDB Endow., April, 2024

Technical Perspective: Synthetic Data Needs a Reproducibility Benchmark.

Xi He

SIGMOD Rec., March, 2024

Differential Privacy with Fine-Grained Provenance: Opportunities and Challenges.

Xi He, Shufan Zhang

IEEE Data Eng. Bull., 2024

Secure Normal Form: Mediation Among Cross Cryptographic Leakages in Encrypted Databases.

Shufan Zhang, Xi He, Ashish Kundu, Sharad Mehrotra, Shantanu Sharma

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

ProBE: Proportioning Privacy Budget for Complex Exploratory Decision Support.

Nada Lahjouji, Sameera Ghayyur, Xi He, Sharad Mehrotra

Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

2023

DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance.

Shufan Zhang, Xi He

Proc. ACM Manag. Data, December, 2023

2022

Don't Be a Tattle-Tale: Preventing Leakages through Data Dependencies on Access Control Protected Data.

Primal Pappachan, Shufan Zhang, Xi He, Sharad Mehrotra

Proc. VLDB Endow., 2022

Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration.

Miti Mazmudar, Thomas Humphries, Jiaxiang Liu, Matthew Rafuse, Xi He

Proc. VLDB Endow., 2022

MIDE: Accuracy Aware Minimally Invasive Data Exploration For Decision Support.

Sameera Ghayyur, Dhrubajyoti Ghosh, Xi He, Sharad Mehrotra

Proc. VLDB Endow., 2022

Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases.

Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman, Jennie Rogers

Proc. Priv. Enhancing Technol., 2022

The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection.

Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, Om Thakkar

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration.

Jiaxiang Liu, Karl Knopf, Yiqing Tan, Bolin Ding, Xi He

Proc. VLDB Endow., 2021

Kamino: Constraint-Aware Differentially Private Data Synthesis.

Chang Ge, Shubhankar Mohapatra, Xi He, Ihab F. Ilyas

Proc. VLDB Endow., 2021

Differential Privacy for Databases.

Joseph P. Near, Xi He

Found. Trends Databases, 2021

Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential Privacy.

Christian Covington, Xi He, James Honaker, Gautam Kamath

CoRR, 2021

DP-cryptography: marrying differential privacy and cryptography in emerging applications.

Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal

Commun. ACM, 2021

DPGraph: A Benchmark Platform for Differentially Private Graph Analysis.

Siyuan Xia, Beizhen Chang, Karl Knopf, Yihan He, Yuchao Tao, Xi He

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Practical Security and Privacy for Database Systems.

Xi He, Jennie Rogers, Johes Bater, Ashwin Machanavajjhala, Chenghong Wang, Xiao Wang

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Federated Deep Learning Architecture for Personalized Healthcare.

Helen H. Chen, Shubhankar Mohapatra, George Michalopoulos, Xi He, Ian McKillop

Proceedings of the Public Health and Informatics, 2021

2020

SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations.

Johes Bater, Yongjoo Park, Xi He, Xiao Wang, Jennie Rogers

Proc. VLDB Endow., 2020

Computing Local Sensitivities of Counting Queries with Joins.

Yuchao Tao, Xi He, Ashwin Machanavajjhala, Sudeepa Roy

Proceedings of the 2020 International Conference on Management of Data, 2020

Crypt?: Crypto-Assisted Differential Privacy on Untrusted Servers.

Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha

Proceedings of the 2020 International Conference on Management of Data, 2020

Linear and Range Counting under Metric-based Local Differential Privacy.

Zhuolun Xiang, Bolin Ding, Xi He, Jingren Zhou

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

PrivateSQL: A Differentially Private SQL Query Engine.

Ios Kotsogiannis, Yuchao Tao, Xi He, Maryam Fanaeepour, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau

Proc. VLDB Endow., 2019

Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing.

Changchang Liu, Xi He, Thee Chanyaswad, Shiqiang Wang, Prateek Mittal

Proc. Priv. Enhancing Technol., 2019

Design of Algorithms under Policy-Aware Local Differential Privacy: Utility-Privacy Trade-offs.

Zhuolun Xiang, Bolin Ding, Xi He, Jingren Zhou

CoRR, 2019

Outis: Crypto-Assisted Differential Privacy on Untrusted Servers.

Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha

CoRR, 2019

Privacy Changes Everything.

Jennie Rogers, Johes Bater, Xi He, Ashwin Machanavajjhala, Madhav Suresh, Xiao Wang

Proceedings of the Heterogeneous Data Management, Polystores, and Analytics for Healthcare, 2019

APEx: Accuracy-Aware Differentially Private Data Exploration.

Chang Ge, Xi He, Ihab F. Ilyas, Ashwin Machanavajjhala

Proceedings of the 2019 International Conference on Management of Data, 2019

2018

Analyzing Your Location Data with Provable Privacy Guarantees.

Ashwin Machanavajjhala, Xi He

Proceedings of the Handbook of Mobile Data Privacy., 2018

Policy Driven Data Sharing with Provable Privacy Guarantees.

Xi He

PhD thesis, 2018

ShrinkWrap: Efficient SQL Query Processing in Differentially Private Data Federations.

Johes Bater, Xi He, William Ehrich, Ashwin Machanavajjhala, Jennie Rogers

Proc. VLDB Endow., 2018

Shrinkwrap: Differentially-Private Query Processing in Private Data Federations.

Johes Bater, Xi He, William Ehrich, Ashwin Machanavajjhala, Jennie Rogers

CoRR, 2018

2017

Private Exploration Primitives for Data Cleaning.

Chang Ge, Ihab F. Ilyas, Xi He, Ashwin Machanavajjhala

CoRR, 2017

Scaling Private Record Linkage using Output Constrained Differential Privacy.

Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava

CoRR, 2017

Composing Differential Privacy and Secure Computation: A Case Study on Scaling Private Record Linkage.

Xi He, Ashwin Machanavajjhala, Cheryl J. Flynn, Divesh Srivastava

Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017

2016

Differential Privacy in the Wild: A tutorial on current practices & open challenges.

Ashwin Machanavajjhala, Xi He, Michael Hay

Proc. VLDB Endow., 2016

A Demonstration of VisDPT: Visual Exploration of Differentially Private Trajectories.

Xi He, Nisarg Raval, Ashwin Machanavajjhala

Proc. VLDB Endow., 2016

2015

DPT: Differentially Private Trajectory Synthesis Using Hierarchical Reference Systems.

Xi He, Graham Cormode, Ashwin Machanavajjhala, Cecilia M. Procopiuc, Divesh Srivastava

Proc. VLDB Endow., 2015

2014

Blowfish privacy: tuning privacy-utility trade-offs using policies.

Xi He, Ashwin Machanavajjhala, Bolin Ding

Proceedings of the International Conference on Management of Data, 2014