Ethan X. Fang
Ethan X. Fang
Assistant Professor at Duke University
Verified email at - Homepage
Cited by
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Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions
M Wang, EX Fang, H Liu
Mathematical Programming 161 (1), 419-449, 2017
Accelerating stochastic composition optimization
M Wang, J Liu, E Fang
Advances in Neural Information Processing Systems 29, 2016
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
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
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), 1-12, 2018
Multilevel stochastic gradient methods for nested composition optimization
S Yang, M Wang, EX Fang
SIAM Journal on Optimization 29 (1), 616-659, 2019
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
Implicit bias of gradient descent based adversarial training on separable data
Y Li, EX Fang, H Xu, T Zhao
Max-norm optimization for robust matrix recovery
EX Fang, H Liu, KC Toh, WX Zhou
Mathematical Programming 167 (1), 5-35, 2018
Using a distributed SDP approach to solve simulated protein molecular conformation problems
X Fang, KC Toh
Distance Geometry, 351-376, 2013
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
Test of significance for high-dimensional longitudinal data
EX Fang, Y Ning, R Li
Annals of statistics 48 (5), 2622, 2020
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
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
Nearly dimension-independent sparse linear bandit over small action spaces via best subset selection
Y Wang, Y Chen, EX Fang, Z Wang, R Li
arXiv preprint arXiv:2009.02003, 2020
High-Dimensional Interactions Detection with Sparse Principal Hessian Matrix.
CY Tang, EX Fang, Y Dong
J. Mach. Learn. Res. 21, 19:1-19:25, 2020
Constructing a confidence interval for the fraction who benefit from treatment, using randomized trial data
EJ Huang, EX Fang, DF Hanley, M Rosenblum
Biometrics 75 (4), 1228-1239, 2019
Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach
EX Fang, H Liu, M Wang
Mathematical Programming 176 (1), 175-205, 2019
A real-time framework for detecting efficiency regressions in a globally distributed codebase
M Valdez-Vivas, C Gocmen, A Korotkov, E Fang, K Goenka, S Chen
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
Fairness-Oriented Learning for Optimal Individualized Treatment Rules
EX Fang, Z Wang, L Wang
Journal of the American Statistical Association, 1-14, 2022
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