2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Adaptive Multi-Branching for Shallow Decision Tree Induction
Hanul Park, Jeonghoon Choi, Juseong Kim +2
Decision trees are attractive for tabular prediction tasks because each prediction follows an interpretable sequence of feature-threshold tests. Under a strict maximum-depth budget…
cs.LG2023
CAST: Cluster-Aware Self-Training for Tabular Data via Reliable Confidence
Minwook Kim, Juseong Kim, Ki Beom Kim +1
Tabular data is one of the most widely used data modalities, encompassing numerous datasets with substantial amounts of unlabeled data. Despite this prevalence, there is a notable…
cs.LG2023★ 2 cited
Revisiting Self-Training with Regularized Pseudo-Labeling for Tabular Data
Minwook Kim, Juseong Kim, Giltae Song
Recent progress in semi- and self-supervised learning has caused a rift in the long-held belief about the need for an enormous amount of labeled data for machine learning and the i…