4 papers · 1 filter
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 (…
Distributed Model Predictive Control for Energy and Comfort Optimization in Large Buildings Using Piecewise Affine Approximation
Hongyi Li, Jun Xu, Jinfeng Liu
The control of large buildings encounters challenges in computational efficiency due to their size and nonlinear components. To address these issues, this paper proposes a Piecewis…
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…
Rotation-Robust Regression with Convolutional Model Trees
Hongyi Li, William Ward Armstrong, Jun Xu
We study rotation-robust learning for image inputs using Convolutional Model Trees (CMTs) [1], whose split and leaf coefficients can be structured on the image grid and transformed…