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Lexin Li

8 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1
  • last author5

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • stat.ME4
  • stat.ML2
  • cs.HC1
  • math.ST1
ORCID 0000-0003-2962-1989
same name
  • Lexin Li — 15 papers, h 33
  • Lexin Li — 5 papers, h 2
  • Lexin Li — 3 papers, h 4
  • Lexin Li — 1 paper, h 3
  • Lexin Li — 1 paper, h 3
  • Lexin Li — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122024
most citedPrincipal support vector machines for linear and nonlinear sufficient dimension reduction

110 citations · 123 across the 8 of their papers we have counts for

collaborators
Showing stat.MEShow all

4 papers · 1 filter

stat.ME2023

Estimation and Inference for High-dimensional Multi-response Growth Curve Model

Xin Zhou, Yin Xia, Lexin Li

A growth curve model (GCM) aims to characterize how an outcome variable evolves, develops and grows as a function of time, along with other predictors. It provides a particularly u…

stat.ME2023

High-dimensional Response Growth Curve Modeling for Longitudinal Neuroimaging Analysis

Lu Wang, Xiang Lyu, Zhengwu Zhang +1

There is increasing interest in modeling high-dimensional longitudinal outcomes in applications such as developmental neuroimaging research. Growth curve model offers a useful tool…

stat.ME2015★ 2 cited

Parsimonious Tensor Response Regression

Lexin Li, Xin Zhang

Aiming at abundant scientific and engineering data with not only high dimensionality but also complex structure, we study the regression problem with a multidimensional array (tens…

stat.ME2014★ 9 cited

Tensor Generalized Estimating Equations for Longitudinal Imaging Analysis

Xiang Zhang, Lexin Li, Hua Zhou +2

In an increasing number of neuroimaging studies, brain images, which are in the form of multidimensional arrays (tensors), have been collected on multiple subjects at multiple time…

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