4 papers
Online Quantile Regression for Nonparametric Additive Models
Haoran Zhan
This paper introduces a projected functional gradient descent algorithm (P-FGD) for training nonparametric additive quantile regression models in online settings. This algorithm ex…
Consistency for Large Neural Networks: Regression and Classification
Haoran Zhan, Yingcun Xia
Although overparameterized models have achieved remarkable practical success, their theoretical properties, particularly their generalization behavior, remain incompletely understo…
Non-asymptotic Properties of Generalized Mondrian Forests in Statistical Learning
Haoran Zhan, Jingli Wang, Yingcun Xia
Random Forests have been extensively used in regression and classification, inspiring the development of various forest-based methods. Among these, Mondrian Forests, derived from t…
Consistency of Oblique Decision Tree and its Boosting and Random Forest
Haoran Zhan, Yu Liu, Yingcun Xia
Classification and Regression Tree (CART), Random Forest (RF) and Gradient Boosting Tree (GBT) are probably the most popular set of statistical learning methods. However, their sta…