Learning Nonlinear Functions Using Regularized Greedy Forest

Learning Nonlinear Functions Using Regularized Greedy Forest

5 September 2011

Tong Zhang

Papers citing "Learning Nonlinear Functions Using Regularized Greedy Forest"

9 / 9 papers shown

Title
Generalizing Gain Penalization for Feature Selection in Tree-based Models Bruna D. Wundervald Andrew C. Parnell Katarina Domijan 22 6 0 12 Jun 2020
Fully-Corrective Gradient Boosting with Squared Hinge: Fast Learning Rates and Early Stopping Jinshan Zeng Min Zhang Shao-Bo Lin 21 18 0 01 Apr 2020
Gradient Boosting Neural Networks: GrowNet Sarkhan Badirli Xuanqing Liu Zhengming Xing Avradeep Bhowmik Khoa D. Doan S. Keerthi FedML 22 83 0 19 Feb 2020
A pathway-based kernel boosting method for sample classification using genomic data Li Zeng Zhaolong Yu Hongyu Zhao 13 3 0 11 Mar 2018
GPU-acceleration for Large-scale Tree Boosting Huan Zhang Si Si Cho-Jui Hsieh 22 80 0 26 Jun 2017
FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification Thomas Keck 14 31 0 20 Sep 2016
Particle Gibbs for Bayesian Additive Regression Trees Balaji Lakshminarayanan Daniel M. Roy Yee Whye Teh 35 21 0 16 Feb 2015
Scalable Nonlinear Learning with Adaptive Polynomial Expansions Alekh Agarwal A. Beygelzimer Daniel J. Hsu John Langford Matus Telgarsky 38 5 0 02 Oct 2014
High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning Francis R. Bach BDL 126 74 0 04 Sep 2009