L
Liping Zhu
Researcher at Renmin University of China
Publications - 82
Citations - 2774
Liping Zhu is an academic researcher from Renmin University of China. The author has contributed to research in topics: Sufficient dimension reduction & Estimator. The author has an hindex of 23, co-authored 82 publications receiving 2222 citations. Previous affiliations of Liping Zhu include Shanghai University of Finance and Economics & East China Normal University.
Papers
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Journal ArticleDOI
Feature Screening via Distance Correlation Learning
Runze Li,Wei Zhong,Liping Zhu +2 more
TL;DR: In this article, a sure independence screening procedure based on distance correlation (DC-SIS) was proposed for ultra-high-dimensional data analysis, which can be used directly to screen grouped predictor variables and multivariate response variables.
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Model-Free Feature Screening for Ultrahigh-Dimensional Data
TL;DR: It is demonstrated that, with the number of predictors growing at an exponential rate of the sample size, the proposed procedure possesses consistency in ranking, which is both useful in its own right and can lead to consistency in selection.
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A Review on Dimension Reduction
Yanyuan Ma,Liping Zhu +1 more
TL;DR: A review of the current literature of dimension reduction with an emphasis on the two most popular models, where the dimension reduction affects the conditional distribution and the conditional mean, respectively, and some unsolved problems in this area for potential future research.
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A Semiparametric Approach to Dimension Reduction
Yanyuan Ma,Liping Zhu +1 more
TL;DR: The semiparametric approach reveals that in the inverse regression context while keeping the estimation structure intact, the common assumption of linearity and/or constant variance on the covariates can be removed at the cost of performing additional nonparametric regression.
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Dimension reduction in regressions through cumulative slicing estimation
TL;DR: In this paper, the authors proposed a complete methodology of cumulative slicing estimation to sufficient dimension reduction, which is termed as cumulative mean estimation, cumulative variance estimation, and cumulative directional regression.