Author

Yijin Ni

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Preprint Aug 2026

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes

The Hilbert-Schmidt independence criterion (HSIC) is taken as an instance of the joint discrepancy $d$ to investigate the statistical efficiency of replacing the conditional formulation and attains fairness-accuracy tradeoffs comparable to conditional-route basel es while reducing per-epoch training time.

Yijin Ni, Xiao-Ming Huo · 0 citations

Preprint Jul 2026

Upper Confidence Bounds for the Prediction Error of Kernel Ridge Regression via Gaussian Refitting

This work proposes a Gaussian refit for kernel ridge regression by Anderson's inequality, which requires no moment assumptions and is calibrated at any confidence level via order statistics, and extends empirically to nonlinear constrained estimators and real spatial data.

Yijin Ni, Xiaoming Huo · 2 citations