5 citations · 5 across the 1 of their papers we have counts for
4 papers
Constructive neural network learning
Shaobo Lin, Jinshan Zeng, Xiaoqin Zhang
In this paper, we aim at developing scalable neural network-type learning systems. Motivated by the idea of "constructive neural networks" in approximation theory, we focus on "con…
Greedy Criterion in Orthogonal Greedy Learning
Lin Xu, Shaobo Lin, Jinshan Zeng +2
Orthogonal greedy learning (OGL) is a stepwise learning scheme that starts with selecting a new atom from a specified dictionary via the steepest gradient descent (SGD) and then bu…
Shrinkage degree in -re-scale boosting for regression
Lin Xu, Shaobo Lin, Yao Wang +1
Re-scale boosting (RBoosting) is a variant of boosting which can essentially improve the generalization performance of boosting learning. The key feature of RBoosting lies in intro…
Re-scale boosting for regression and classification
Shaobo Lin, Yao Wang, Lin Xu
Boosting is a learning scheme that combines weak prediction rules to produce a strong composite estimator, with the underlying intuition that one can obtain accurate prediction rul…