David Pujol

According to our database, David Pujol authored at least 10 papers between 2019 and 2023.

Collaborative distances:

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

2023

PreFair: Privately Generating Justifiably Fair Synthetic Data.

David Pujol, Amir Gilad, Ashwin Machanavajjhala

Proc. VLDB Endow., 2023

Private Proof-of-Stake Blockchains using Differentially-private Stake Distortion.

Chenghong Wang, David Pujol, Kartik Nayak, Ashwin Machanavajjhala

IACR Cryptol. ePrint Arch., 2023

Privately Answering Queries on Skewed Data via Per Record Differential Privacy.

Jeremy Seeman, William Sexton, David Pujol, Ashwin Machanavajjhala

CoRR, 2023

Publishing Wikipedia usage data with strong privacy guarantees.

Temilola Adeleye, Skye Berghel, Damien Desfontaines, Michael Hay, Isaac Johnson, Cléo Lemoisson, Ashwin Machanavajjhala, Tom Magerlein, Gabriele Modena, David Pujol, Daniel Simmons-Marengo, Hal Triedman

CoRR, 2023

2022

Multi-Analyst Differential Privacy for Online Query Answering.

David Pujol, Albert Sun, Brandon Fain, Ashwin Machanavajjhala

Proc. VLDB Endow., 2022

2021

Budget Sharing for Multi-Analyst Differential Privacy.

David Pujol, Yikai Wu, Brandon Fain, Ashwin Machanavajjhala

Proc. VLDB Endow., 2021

Equity and Privacy: More Than Just a Tradeoff.

David Pujol, Ashwin Machanavajjhala

IEEE Secur. Priv., 2021

2020

Poirot: private contact summary aggregation: poster abstract.

Yanping Zhang, Chenghong Wang, David Pujol, Johes Bater, Matthew Lentz, Ashwin Machanavajjhala, Kartik Nayak, Lavanya Vasudevan, Jun Yang

Proceedings of the SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems, 2020

Fair decision making using privacy-protected data.

David Pujol, Ryan McKenna, Satya Kuppam, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau

Proceedings of the FAT* '20: Conference on Fairness, 2020

2019

Answering Summation Queries for Numerical Attributes under Differential Privacy.

Yikai Wu, David Pujol, Ios Kotsogiannis, Ashwin Machanavajjhala

CoRR, 2019