Publications

Fast Private Adaptive Query Answering for Large Data Domains
Miguel Fuentes, Brett Mullins, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon
International Conference on Artificial Intelligence and Statistics (AISTATS), 2026
Paper

Efficient and Private Marginal Reconstruction with Local Non-negativity
Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon
Advances in Neural Information Processing Systems (NeurIPS), 2024
Paper | Slides | Code | Summary | Video

Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
Miguel Fuentes, Brett Mullins, Ryan McKenna, Daniel Sheldon, Gerome Miklau
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Paper | Code | Summary

Quantifying Uncertainty of Unsupported Linear Queries for Private Query Release
Brett Mullins, Daniel Sheldon, Gerome Miklau
Theory and Practice of Differential Privacy (TPDP), 2023
Paper

The Shape of Explanations: A Topological Account of Rule-Based Explanations in Machine Learning
Brett Mullins
AAAI 2023 Workshop on Representation Learning for Responsible Human-Centric AI (R2HCAI), 2023
Paper | Summary | Video

AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Ryan McKenna, Brett Mullins, Daniel Sheldon, Gerome Miklau
Proceedings of the 48th International Conference on Very Large Databases (VLDB), 2022
Paper | Code | Summary

Economic Mobility and the Great Recession
Brett Mullins, David Sjoquist, Sally Wallace
Social Science Quarterly, 2021
Paper | Code