4 papers
FUSE: Feature-Wise Unified Specialization with Cross-Column Exchange for Mixed-Type Tabular Flow Matching
Suman Cha, Seongchan Lee, Dohyun Ko +1
Generating mixed-type tabular data requires jointly modeling diverse feature distributions and their complex cross-column dependencies. Variational flow matching handles distinct e…
More Permutations Do Not Always Increase Power: Non-monotonicity in Monte Carlo Permutation Tests
Suman Cha, Seongchan Lee, Antonin Schrab +1
Monte Carlo permutation tests are a cornerstone of valid, model-free statistical inference. A widely held practical intuition is that increasing the number of sampled permutations…
General Frameworks for Conditional Two-Sample Testing
Seongchan Lee, Suman Cha, Ilmun Kim
We study the problem of conditional two-sample testing, which aims to determine whether two populations have the same distribution after accounting for confounding factors. This pr…
Learning Majority-to-Minority Transformations with MMD and Triplet Loss for Imbalanced Classification
Suman Cha, Hyunjoong Kim
Class imbalance in supervised classification often degrades model performance by biasing predictions toward the majority class, particularly in critical applications such as medica…