4 citations · 4 across the 2 of their papers we have counts for
4 papers
Nonparametric Feature Selection by Random Forests and Deep Neural Networks
Xiaojun Mao, Liuhua Peng, Zhonglei Wang
Random forests are a widely used machine learning algorithm, but their computational efficiency is undermined when applied to large-scale datasets with numerous instances and usele…
Bootstrap inference for the finite population total under complex sampling designs
Zhonglei Wang, Jae Kwang Kim, Liuhua Peng
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results under complex survey sampling. Most studies about bootstrap-based inference are de…
Variable Importance Assessments and Backward Variable Selection for High-Dimensional Data
Liuhua Peng, Long Qu, Dan Nettleton
Variable selection in high-dimensional scenarios is of great interested in statistics. One application involves identifying differentially expressed genes in genomic analysis. Exis…
Distributed Statistical Inference for Massive Data
Song Xi Chen, Liuhua Peng
This paper considers distributed statistical inference for general symmetric statistics %that encompasses the U-statistics and the M-estimators in the context of massive data where…