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02/09/2022
Longitudinal regression of covariance matrix outcomes
In this study, a longitudinal regression model for covariance matrix out...
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04/14/2021
Regularized regression on compositional trees with application to MRI analysis
A compositional tree refers to a tree structure on a set of random varia...
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04/01/2021
Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors
Brain segmentation at different levels is generally represented as hiera...
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10/28/2020
Micromobility in Smart Cities: A Closer Look at Shared Dockless E-Scooters via Big Social Data
The micromobility is shaping first- and last-mile travels in urban areas...
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07/24/2020
Principal Regression for High Dimensional Covariance Matrices
This manuscript presents an approach to perform generalized linear regre...
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05/27/2020
AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph
This paper presents a fully automatic framework for extracting editable ...
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05/23/2020
Mathematical Modeling of Business Reopening when Facing SARS-CoV-2 Pandemic: Protection, Cost and Risk
The sudden onset of the coronavirus (SARS-CoV-2) pandemic has resulted i...
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05/23/2020
A key question to business owners facing SARS-CoV-2 pandemics: When to reopen my business?
The sudden onset of the coronavirus (SARS-CoV-2) pandemic has resulted i...
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04/04/2019
Towards 3D Human Shape Recovery Under Clothing
We present a learning-based scheme for robustly and accurately estimatin...
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05/17/2018
Functional Mediation Analysis with an Application to Functional Magnetic Resonance Imaging Data
Causal mediation analysis is widely utilized to separate the causal effe...
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09/15/2017
Granger Mediation Analysis of Multiple Time Series with an Application to fMRI
It becomes increasingly popular to perform mediation analysis for comple...
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03/24/2016
Pathway Lasso: Estimate and Select Sparse Mediation Pathways with High Dimensional Mediators
In many scientific studies, it becomes increasingly important to delinea...
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08/08/2015
Minimax Optimal Variable Clustering in G-Block Correlation Models via Cord
The goal of variable clustering is to partition a random vector X∈ R^p ...
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03/19/2014
A Hierarchical Graphical Model for Big Inverse Covariance Estimation with an Application to fMRI
Brain networks has attracted the interests of many neuroscientists. From...
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03/17/2012