2024
Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning
Deng S, Ning Y, Zhao J, Zhang H. Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning. Journal Of The American Statistical Association 2024, ahead-of-print: 1-12. DOI: 10.1080/01621459.2023.2277409.Peer-Reviewed Original ResearchSemi-supervised estimatorConditional mean functionMean functionSupervised estimationParameters of linear modelsSemi-supervised learningRegression parametersEstimation problemLinear modelSupplementary materialsTheoretical resultsParameter estimationSemi-supervised settingUnlabeled dataLabeled dataEstimationMinimaxMisspecificationNumerical simulationsDataFunctionLearningProblemData analysis
2016
Variable Selection With Prior Information for Generalized Linear Models via the Prior LASSO Method
Jiang Y, He Y, Zhang H. Variable Selection With Prior Information for Generalized Linear Models via the Prior LASSO Method. Journal Of The American Statistical Association 2016, 111: 355-376. PMID: 27217599, PMCID: PMC4874534, DOI: 10.1080/01621459.2015.1008363.Peer-Reviewed Original ResearchLeast angle regressionGeneralized linear modelPrior informationExtension of LassoLinear modelPopular statistical toolWhole solution pathAsymptotic theoryAngle regressionEstimate parametersVariable selectionSolution pathStatistical toolsCriterion functionLASSOLASSO methodReal dataSimulation resultsGreater robustnessVariables of interestMisspecificationEstimatorModelBiomedical studiesVariables