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cs.LG2026
Hinge Regression Trees and HRT-Boost: Newton-Optimized Oblique Learning for Compact Tabular Models
Hongyi Li, Jun Xu, Hong Yan
Learning high-quality oblique decision trees remains a significant challenge due to the discrete and non-convex nature of split optimization. We present the Hinge Regression Tree (…
cs.LG2026
Hinge Regression Tree: A Newton Method for Oblique Regression Tree Splitting
Hongyi Li, Han Lin, Jun Xu
Oblique decision trees combine the transparency of trees with the power of multivariate decision boundaries, but learning high-quality oblique splits is NP-hard, and practical meth…