2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions
Alycia N. Carey, Minh-Hao Van, Xintao Wu
How to properly set the privacy parameter in differential privacy (DP) has been an open question in DP research since it was first proposed in 2006. In this work, we demonstrate th…
cs.LG2023
A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias
Huy Mai, Wen Huang, Wei Du +1
The shift between the training and testing distributions is commonly due to sample selection bias, a type of bias caused by non-random sampling of examples to be included in the tr…
cs.AI2022★ 2 cited
The Fairness Field Guide: Perspectives from Social and Formal Sciences
Alycia N. Carey, Xintao Wu
Over the past several years, a slew of different methods to measure the fairness of a machine learning model have been proposed. However, despite the growing number of publications…