Papers
1–3 of 3Research Paper·Mar 16, 2026
Sampling-guided exploration of active feature selection policies
Determining the most appropriate features for machine learning predictive models is challenging regarding performance and feature acquisition costs. In particular, global feature choice is limited giv...
6.0 viability
Research Paper·Mar 9, 2026
A New Modeling to Feature Selection Based on the Fuzzy Rough Set Theory in Normal and Optimistic States on Hybrid Information Systems
Considering the high volume, wide variety, and rapid speed of data generation, investigating feature selection methods for big data presents various applications and advantages. By removing irrelevant...
4.0 viability
Research Paper·Mar 17, 2026
Safe Distributionally Robust Feature Selection under Covariate Shift
In practical machine learning, the environments encountered during the model development and deployment phases often differ, especially when a model is used by many users in diverse settings. Learning...
2.0 viability