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cs.LG2025
Safe Screening Rules for Group SLOPE
Runxue Bao, Quanchao Lu, Yanfu Zhang
Variable selection is a challenging problem in high-dimensional sparse learning, especially when group structures exist. Group SLOPE performs well for the adaptive selection of gro…
cs.CL2025
Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
Haoyan Yang, Runxue Bao, Cao Xiao +4
LLM-as-a-Judge has emerged as a promising tool for automatically evaluating generated outputs, but its reliability is often undermined by potential biases in judgment. Existing eff…
cs.LG2025
Safe Screening Rules for Group OWL Models
Runxue Bao, Quanchao Lu, Yanfu Zhang
Group Ordered Weighted -Norm (Group OWL) regularized models have emerged as a useful procedure for high-dimensional sparse multi-task learning with correlated features. Prox…