2 papers
stat.ML2025
Kernel-based Equalized Odds: A Quantification of Accuracy-Fairness Trade-off in Fair Representation Learning
Yijin Ni, Xiaoming Huo
This paper introduces a novel kernel-based formulation of the Equalized Odds (EO) criterion, denoted as , for fair representation learning (FRL) in supervised settings. The c…
cs.LG2025
A Uniform Concentration Inequality for Kernel-Based Two-Sample Statistics
Yijin Ni, Xiaoming Huo
In many contemporary statistical and machine learning methods, one needs to optimize an objective function that depends on the discrepancy between two probability distributions. Th…