Ethan X. Fang

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Han LiuOrrington Lunt Professor of Computer Science, Statistics and Data Science, Northwestern UniversityVerifierad e-postadress på northwestern.edu
Mengdi WangCenter for Statistics & Machine Learning, ECE, Princeton UniversityVerifierad e-postadress på princeton.edu
Tuo ZhaoAssociate Professor, Georgia TechVerifierad e-postadress på gatech.edu
Zhaoran WangAssociate Professor at Northwestern UniversityVerifierad e-postadress på northwestern.edu
Runze LiPenn State UnviersityVerifierad e-postadress på psu.edu
Yang NingCornell UniversityVerifierad e-postadress på cornell.edu
Shuoguang YangThe Hong Kong University of Science and TechnologyVerifierad e-postadress på ust.hk
Junwei LuAssistant Professor of Biostatistics, Harvard T.H. Chan School of Public HealthVerifierad e-postadress på hsph.harvard.edu
Yan LiGeorgia Institute of TechnologyVerifierad e-postadress på gatech.edu
Michael RosenblumProfessor of Biostatistics, Johns Hopkins UniversityVerifierad e-postadress på jhsph.edu
Ji LiuMetaVerifierad e-postadress på meta.com
Min-Dian LiHarvard TH Chan School of Public HealthVerifierad e-postadress på hsph.harvard.edu
Cong ShiManagement, Miami Herbert Business School, University of MiamiVerifierad e-postadress på bus.miami.edu
Kim-Chuan TohProfessor of Mathematics, National University of SingaporeVerifierad e-postadress på nus.edu.sg
Xiaoming YuanThe University of Hong KongVerifierad e-postadress på hku.hk
Huan XuAlibaba IncVerifierad e-postadress på alibaba-inc.com
Lin F. Yang (杨林)Assistant Professor, Department of Electrical and Computer Engineering @ UCLAVerifierad e-postadress på ee.ucla.edu
Matey NeykovAssistant Professor, Department of Statistics and Data Science, Northwestern UniversityVerifierad e-postadress på northwestern.edu
Emily HuangAssistant Professor of Statistics, Wake Forest UniversityVerifierad e-postadress på wfu.edu
Xiaoyong YangYale UniversityVerifierad e-postadress på yale.edu

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Ethan X. Fang

Associate Professor at Duke University

Verifierad e-postadress på duke.edu - Startsida

Statistics Biostatistics Optimization


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions M Wang, EX Fang, H Liu Mathematical Programming 161, 419-449, 2017	295	2017
Accelerating stochastic composition optimization M Wang, J Liu, EX Fang Journal of Machine Learning Research 18 (105), 1-23, 2017	172	2017
Generalized alternating direction method of multipliers: new theoretical insights and applications EX Fang, B He, H Liu, X Yuan Mathematical programming computation 7 (2), 149-187, 2015	123	2015
Testing and confidence intervals for high dimensional proportional hazards model EX Fang, Y Ning, H Liu Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2018	87	2018
Multilevel stochastic gradient methods for nested composition optimization S Yang, M Wang, EX Fang SIAM Journal on Optimization 29 (1), 616-659, 2019	68	2019
Adipocyte OGT governs diet-induced hyperphagia and obesity MD Li, NB Vera, Y Yang, B Zhang, W Ni, E Ziso-Qejvanaj, S Ding, ... Nature communications 9 (1), 5103, 2018	61	2018
Implicit bias of gradient descent based adversarial training on separable data Y Li, E Fang, H Xu, T Zhao International Conference on Learning Representations, 2020	51*	2020
Test of significance for high-dimensional longitudinal data EX Fang, Y Ning, R Li Annals of statistics 48 (5), 2622, 2020	37	2020
Misspecified nonconvex statistical optimization for sparse phase retrieval Z Yang, LF Yang, EX Fang, T Zhao, Z Wang, M Neykov Mathematical Programming, 1-27, 2019	37*	2019
Fairness-oriented learning for optimal individualized treatment rules EX Fang, Z Wang, L Wang Journal of the American Statistical Association 118 (543), 1733-1746, 2023	31	2023
Max-norm optimization for robust matrix recovery EX Fang, H Liu, KC Toh, WX Zhou Mathematical Programming 167, 5-35, 2018	31	2018
Using a distributed SDP approach to solve simulated protein molecular conformation problems X Fang, KC Toh Distance Geometry: Theory, Methods, and Applications, 351-376, 2012	28	2012
Lagrangian inference for ranking problems Y Liu, EX Fang, J Lu Operations research 71 (1), 202-223, 2023	25	2023
Nearly dimension-independent sparse linear bandit over small action spaces via best subset selection Y Chen, Y Wang, EX Fang, Z Wang, R Li Journal of the American Statistical Association 119 (545), 246-258, 2024	23*	2024
Inequality in treatment benefits: Can we determine if a new treatment benefits the many or the few? EJ Huang, EX Fang, DF Hanley, M Rosenblum Biostatistics 18 (2), 308-324, 2017	23	2017
Optimal, two-stage, adaptive enrichment designs for randomized trials, using sparse linear programming M Rosenblum, EX Fang, H Liu Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020	19	2020
High-dimensional interactions detection with sparse principal hessian matrix CY Tang, EX Fang, Y Dong Journal of Machine Learning Research 21 (19), 1-25, 2020	17	2020
Offline personalized pricing with censored demand Z Qi, J Tang, E Fang, C Shi Offline Personalized Pricing with Censored Demand: Qi, Zhengling\| uTang …, 2022	13	2022
Implicit regularization of bregman proximal point algorithm and mirror descent on separable data Y Li, C Ju, EX Fang, T Zhao arXiv preprint arXiv:2108.06808, 2021	9	2021
Mining massive amounts of genomic data: a semiparametric topic modeling approach EX Fang, MD Li, MI Jordan, H Liu Journal of the American Statistical Association 112 (519), 921-932, 2017	9	2017

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