Publications

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

See my CV for a full list of publications, including those prior to 2020