Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
Weight-Informed Self-Explaining Clustering for Mixed-Type Tabular Data
Lehao Li, Qiang Huang, Yihao Ang +3
Clustering mixed-type tabular data is fundamental for exploratory analysis, yet remains challenging due to misaligned numerical-categorical representations, uneven and context-depe…
cs.LG2026
TreeGrad-Ranker: Feature Ranking via -Time Gradients for Decision Trees
Weida Li, Yaoliang Yu, Bryan Kian Hsiang Low
We revisit the use of probabilistic values, which include the well-known Shapley and Banzhaf values, to rank features for explaining the local predicted values of decision trees. T…
cs.LG2019
A Unifying Framework of Bilinear LSTMs
Mohit Rajpal, Bryan Kian Hsiang Low
This paper presents a novel unifying framework of bilinear LSTMs that can represent and utilize the nonlinear interaction of the input features present in sequence datasets for ach…