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Hao-Jie Ren

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Preprint Oct 2026

Controlling the False Discovery Rate via Model-Agnostic Importance Measures

Selecting covariates while controlling the false discovery rate (FDR) is critical for interpretable scientific discovery, especially with complex machine learning models. Traditional variable selection methods often rely on specific model assumptions, while Model-X knockoffs provide a general way that leverages knowled...

Meng-Tao Wen, Hao-Jie Ren, Chang-Liang Zou · 0 citations
#machine learning Preprint Oct 2026

Minimum Volume Optimal Transport for Multivariate Conformal Prediction

Optimal transport (OT) enables multivariate conformal prediction (CP) to construct flexible prediction sets that reflect the underlying complex distributional geometry while retaining distribution-free coverage guarantees. Existing OT-based methods typically rely on a fixed Euclidean transport cost, which can be subopt...

Chu-Chen Zhang, Hao-Jie Ren, Zhao-Jun Wang et al. · 0 citations

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