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cs.LG2026
Surprise-Guided MergeSort: Budget-Efficient Human-in-the-Loop Ranking via Adaptive Comparison Scheduling
Yujin Park, Haejun Chung, Ikbeom Jang
Pairwise comparison is the gold standard for subjective ranking tasks; however, exhaustive annotation requires a massive number of human comparisons (). While sorting-based…
cs.LG2026
When, Where, and How: Adaptive Binning for Tabular Self-Supervised Learning
Daehwan Kim, Haejun Chung, Ikbeom Jang
Medical tabular data are ubiquitous in clinical research, but deep learning for tables remains underexplored because reliable labels often require costly expert adjudication, even…
cs.LG2025
Ordinal-Aware Calibration for Ordinal Classification
Daehwan Kim, Haejun Chung, Ikbeom Jang
Deep neural networks frequently produce overconfident, miscalibrated predictions. In ordinal classification, predictions must also adhere to a unimodal and order-consistent structu…