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20172026
most citedPrincipal component analysis for big data

18 citations · 28 across the 12 of their papers we have counts for

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6 papers · 1 filter

stat.ME2021

Distributed Adaptive Huber Regression

Jiyu Luo, Qiang Sun, Wenxin Zhou

Distributed data naturally arise in scenarios involving multiple sources of observations, each stored at a different location. Directly pooling all the data together is often prohi…

stat.ME2021

Adaptive Capped Least Squares

Qiang Sun, Rui Mao, Wen-Xin Zhou

This paper proposes the capped least squares regression with an adaptive resistance parameter, hence the name, adaptive capped least squares regression. The key observation is, by…

stat.ME20191 cited

Modeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity

Zhenhua Lin, Dehan Kong, Qiang Sun

In neuroscience, functional brain connectivity describes the connectivity between brain regions that share functional properties. Neuroscientists often characterize it by a time se…

stat.ME2019

Bayesian Factor-adjusted Sparse Regression

Jianqing Fan, Bai Jiang, Qiang Sun

This paper investigates the high-dimensional linear regression with highly correlated covariates. In this setup, the traditional sparsity assumption on the regression coefficients…

stat.ME2018

User-Friendly Covariance Estimation for Heavy-Tailed Distributions

Yuan Ke, Stanislav Minsker, Zhao Ren +2

We offer a survey of recent results on covariance estimation for heavy-tailed distributions. By unifying ideas scattered in the literature, we propose user-friendly methods that fa…

stat.ME201818 cited

Principal component analysis for big data

Jianqing Fan, Qiang Sun, Wen-Xin Zhou +1

Big data is transforming our world, revolutionizing operations and analytics everywhere, from financial engineering to biomedical sciences. The complexity of big data often makes d…