4 citations · 10 across the 7 of their papers we have counts for
Showing stat.MEShow all
3 papers · 1 filter
stat.ME2026
Conformalized Robust Principal Component Analysis
Liangliang Yuan, Lei Wang, Quan Kong +1
Robust principal component analysis (RPCA) is a widely used technique for recovering low-rank structure from matrices with missing entries and sparse, possibly large-magnitude corr…
stat.ME2023★ 1 cited
Statistical Inference for Ultrahigh Dimensional Location Parameter Based on Spatial Median
Guanghui Cheng, Liuhua Peng, Changliang Zou
Motivated by the widely used geometric median-of-means estimator in machine learning, this paper studies statistical inference for ultrahigh dimensionality location parameter based…
stat.ME2018
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…