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stat.ML2026
Fairness May Backfire: When Leveling-Down Occurs in Fair Machine Learning
Yi Yang, Xiangyu Chang, Pei-yu Chen
As machine learning (ML) systems increasingly shape access to credit, jobs, and other opportunities, the fairness of algorithmic decisions has become a central concern. Yet it rema…
stat.ML2026
Beyond Cross-Validation: Adaptive Parameter Selection for Kernel-Based Gradient Descents
Xiaotong Liu, Yunwen Lei, Xiangyu Chang +1
This paper proposes a novel parameter selection strategy for kernel-based gradient descent (KGD) algorithms, integrating bias-variance analysis with the splitting method. We introd…
stat.ML2025
Bayes-Optimal Fair Classification with Multiple Sensitive Features
Yi Yang, Yinghui Huang, Xiangyu Chang
Existing theoretical work on Bayes-optimal fair classifiers usually considers a single (binary) sensitive feature. In practice, individuals are often defined by multiple sensitive…