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Shuangge Ma

Researcher at Yale University

Publications -  368
Citations -  13115

Shuangge Ma is an academic researcher from Yale University. The author has contributed to research in topics: Feature selection & Covariate. The author has an hindex of 47, co-authored 338 publications receiving 10622 citations. Previous affiliations of Shuangge Ma include The Catholic University of America & Taiyuan University of Technology.

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Adaptive Lasso for sparse high-dimensional regression models

TL;DR: The adaptive Lasso has the oracle property even when the number of covariates is much larger than the sample size, and under a partial orthogonality condition in which the covariates with zero coefficients are weakly correlated with the covariate with nonzero coefficients, marginal regression can be used to obtain the initial estimator.
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Regularized gene selection in cancer microarray meta-analysis.

TL;DR: Simulation studies and analyses of multiple pancreatic and liver cancer experiments demonstrate the superior performance of the Meta Threshold Gradient Descent Regularization approach for gene selection in the meta analysis of cancer microarray data.
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Diverse Functional Autoantibodies in Patients with COVID-19.

TL;DR: In this article, a high-throughput autoantibody discovery technique known as rapid extracellular antigen profiling was used to screen a cohort of 194 individuals infected with SARS-CoV-2, comprising 172 patients with COVID-19 and 22 health care workers with mild disease or asymptomatic infection, for auto-antibodies against 2,770 proteins (members of the exoproteome).
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Asymptotic properties of bridge estimators in sparse high-dimensional regression models

TL;DR: In this paper, the authors studied the asymptotic properties of bridge estimators in sparse, high-dimensional, linear regression models when the number of covariates may increase to infinity with the sample size.