5 citations · 6 across the 2 of their papers we have counts for
4 papers
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes
Di Wang, Yao Wang, Shao-Bo Lin
In recent years, large amounts of electronic health records (EHRs) concerning chronic diseases have been collected to facilitate medical diagnosis. Modeling the dynamic properties…
Divide and Conquer Local Average Regression
Xiangyu Chang, Shaobo Lin, Yao Wang
The divide and conquer strategy, which breaks a massive data set into a se- ries of manageable data blocks, and then combines the independent results of data blocks to obtain a fin…
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…