3 papers
cs.LG2025
FairNet: Dynamic Fairness Correction without Performance Loss via Contrastive Conditional LoRA
Songqi Zhou, Zeyuan Liu, Benben Jiang
Ensuring fairness in machine learning models is a critical challenge. Existing debiasing methods often compromise performance, rely on static correction strategies, and struggle wi…
cs.LG2024
Adaptive Boosting with Fairness-aware Reweighting Technique for Fair Classification
Xiaobin Song, Zeyuan Liu, Benben Jiang
Machine learning methods based on AdaBoost have been widely applied to various classification problems across many mission-critical applications including healthcare, law and finan…
cs.LG2023
Parallel Bayesian Optimization Using Satisficing Thompson Sampling for Time-Sensitive Black-Box Optimization
Xiaobin Song, Benben Jiang
Bayesian optimization (BO) is widely used for black-box optimization problems, and have been shown to perform well in various real-world tasks. However, most of the existing BO met…