Jelena Bradic

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Yinchu ZhuAssistant Professor of Economics, Brandeis UniversityE-mail confirmado em brandeis.edu
Jianqing FanProfessor of Statistics, Professor of Finance, Princeton UniversityE-mail confirmado em princeton.edu
Jue HouUniversity of Minnesota Twin CitiesE-mail confirmado em umn.edu
Jiancheng JiangUniversity of North CarolinaE-mail confirmado em uncc.edu
Davide VivianoDepartment of Economics, Harvard UniversityE-mail confirmado em fas.harvard.edu
Runze LiPenn State UnviersityE-mail confirmado em psu.edu
Bo PengUniversity of MinnesotaE-mail confirmado em umn.edu
Yi YuDepartment of Statistics, University of WarwickE-mail confirmado em warwick.ac.uk
Rui SongNorth Carolina State UniversityE-mail confirmado em ncsu.edu
Mladen KolarUniversity of Southern CaliforniaE-mail confirmado em usc.edu
Stefan WagerGraduate School of Business, Stanford UniversityE-mail confirmado em stanford.edu
Ilya O. RyzhovRobert H. Smith School of Business, University of MarylandE-mail confirmado em umd.edu
Whitney NeweyProfessor of Economics, MITE-mail confirmado em mit.edu
Victor ChernozhukovProfessor, Department of Economics + Center for Statistics and Data Science, MIT;E-mail confirmado em mit.edu
Jiaqi GuoAmazonE-mail confirmado em amazon.com
Jiayi HouUniversity of California, San DiegoE-mail confirmado em ucsd.edu
James D MurphyUniversity of California San DiegoE-mail confirmado em ucsd.edu
Bo HanAalborg UniversityE-mail confirmado em es.aau.dk

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Jelena Bradic

Full Professor of Statistics, Mathematics Department & Halicioglu Data Science Institute

E-mail confirmado em math.ucsd.edu - Página inicial

Causal Inference High Dimensional Inference Robustness Machine Learning Missing Data


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Penalized composite quasi-likelihood for ultrahigh dimensional variable selection J Bradic, J Fan, W Wang Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2011	204	2011
Regularization for Cox’s proportional hazards model with NP-dimensionality J Bradic, J Fan, J Jiang Annals of statistics 39 (6), 3092, 2011	182	2011
Linear Hypothesis Testing in Dense High-Dimensional Linear Models Y Zhu, J Bradic Journal of the American Statistical Association: Theory and Methods 113 (524 …, 2018	103	2018
A Tuning-free Robust and Efficient Approach to High-dimensional Regression (with a discussion) L Wang, B Peng, J Bradic, R Li, Y Wu Journal of the American Statistical Association: Theory and Methods, 2020	65*	2020
Cultivating disaster donors: A case application of scalable analytics on massive data IO Ryzhov, B Han, J Bradic Management Science, 2013	61*	2013
Sparsity Double Robust Inference of Average Treatment Effects J Bradic, S Wager, Y Zhu https://arxiv.org/abs/1905.00744, 2019	59	2019
Significance testing in non-sparse high-dimensional linear models Y Zhu, J Bradic Electronic Journal of Statistics 12 (2), 3312-3364, 2018	54*	2018
High-dimensional semi-supervised learning: in search for optimal inference of the mean Y Zhang, J Bradic https://arxiv.org/abs/1902.00772, 2019	53	2019
Confidence intervals for high-dimensional Cox model Y Yu, J Bradic, RJ Samworth Statistica Sinica, 2018	43	2018
Boosting in the presence of outliers: adaptive classification with non-convex loss functions AH Li, J Bradic Journal of the American Statistical Association: Theory and Methods 113 (522 …, 2018	41	2018
Fair Policy Targeting D Viviano, J Bradic arXiv preprint arXiv: 2005.12395, 2020	32*	2020
Uniform inference for high-dimensional quantile regression: linear functionals and regression rank scores J Bradic, M Kolar arXiv preprint arXiv:1702.06209, 55, 2017	31	2017
Synthetic learner: model-free inference on treatments over time D Viviano, J Bradic https://arxiv.org/abs/1904.01490, 2019	30*	2019
Testability of high-dimensional linear models with non-sparse structures J Bradic, J Fan, Y Zhu https://arxiv.org/abs/1802.09117, 2018	29*	2018
Double robust semi-supervised inference for the mean: selection bias under MAR labeling with decaying overlap Y Zhang, A Chakrabortty, J Bradic Information and Inference: A Journal of the IMA 12 (3), 2066-2159, 2023	24	2023
Minimax semiparametric learning with approximate sparsity J Bradic, V Chernozhukov, WK Newey, Y Zhu arXiv preprint arXiv:1912.12213, 2019	24	2019
Fixed effects testing in high-dimensional linear mixed models J Bradic, G Claeskens, T Gueuning Journal of the American Statistical Association: Theory & Methods, 2017	24	2017
Robustness in sparse high-dimensional linear models: Relative efficiency and robust approximate message passing J Bradic	24*	2016
Censored quantile regression forests AH Li, J Bradic https://arxiv.org/abs/1902.03327, 2019	23	2019
Randomized maximum-contrast selection: subagging for large-scale regression J Bradic Electronic Journal of Statistics 10 (1), 121-170, 2016	21*	2016

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