3 papers
stat.ML2026
A nonparametric two-sample test using a parametric integral probability metric
Yuha Park, Yongdai Kim
Detecting distributional differences between two independent samples is a fundamental problem in statistics and machine learning. Nonparametric two-sample testing provides a princi…
stat.ML2025
Tensor Product Neural Networks for Functional ANOVA Model
Seokhun Park, Insung Kong, Yongchan Choi +2
Interpretability for machine learning models is becoming more and more important as machine learning models become more complex. The functional ANOVA model, which decomposes a high…
stat.ML2024
META-ANOVA: Screening interactions for interpretable machine learning
Yongchan Choi, Seokhun Park, Chanmoo Park +2
There are two things to be considered when we evaluate predictive models. One is prediction accuracy,and the other is interpretability. Over the recent decades, many prediction mod…