1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
Miguel Fuentes, Brett Mullins, Ryan McKenna +2
Mechanisms for generating differentially private synthetic data based on marginals and graphical models have been successful in a wide range of settings. However, one limitation of…
cs.LG2023★ 1 cited
The Shape of Explanations: A Topological Account of Rule-Based Explanations in Machine Learning
Brett Mullins
Rule-based explanations provide simple reasons explaining the behavior of machine learning classifiers at given points in the feature space. Several recent methods (Anchors, LORE,…