Ethan Xingyuang Fang

Assistant Professor of Statistics

Ethan Xingyuang Fang

Most Recent Publications

Optimal, two‐stage, adaptive enrichment designs for randomized trials, using sparse linear programming

Michael Rosenblum, Xingyuan Fang, H Liu, Journal of Royal Statistical Society: Series B

High-dimensional Interactions Detection with Sparse Principal Hessian Matrix

Cheng Yong Tang, Xingyuan Fang, Yuexiao Dong, Journal of Machine Learning Research

A Smoothed Augmented Lagrangian Framework for Convex Optimization with Nonsmooth Constraints

Peixuan Zhang, Vinayak V. Shanbhag, Ethan X. Fang, 2025, Journal of Scientific Computing

Data-Driven Compositional Optimization in Misspecified Regimes

Shuoguang Yang, Ethan X. Fang, Vinayak V. Shanbhag, 2025, Operations Research on p. 1395-1411

Offline Feature-Based Pricing Under Censored Demand: A Causal Inference Approach

Jingwen Tang, Zhengling Qi, Ethan Fang, Cong Shi, 2025, Manufacturing and Service Operations Management on p. 535-553

Effectiveness and cost-effectiveness of an integrated digital psychological intervention (EmoEase) in Chinese chronic obstructive pulmonary disease patients: Study protocol of a randomized controlled trial

Simiao Chen, Wenjin Chen, Yanfei Li, Yiwen Yu, Qiushi Chen, Lirui Jiao, Ke Huang, Xunliang Tong, Pascal Geldsetzer, Aditi Bunker, Xingyuan Fang, Shu Jing, Yuhao Liu, Yanming Li, Liu He, Chao Wang, Weiyu Wang, Zhoutao Zheng, Shiyu Zhang, Jinghan Zhao, Ting Yang, Till Bärnighausen, Chen Wang, 2024, Digital Health

Deep Spatial Q-Learning for Infectious Disease Control

Zhishuai Liu, Jesse Clifton, Eric B. Laber, John Drake, Ethan X. Fang, 2023, Journal of Agricultural, Biological, and Environmental Statistics on p. 749-773

Robust matrix estimations meet Frank–Wolfe algorithm

Naimin Jing, Ethan X. Fang, Cheng Yong Tang, 2023, Machine Learning on p. 2723-2760

Fairness-Oriented Learning for Optimal Individualized Treatment Rules

Ethan X. Fang, Zhaoran Wang, Lan Wang, 2023, Journal of the American Statistical Association on p. 1733-1746

PASTA: Pessimistic Assortment Optimization

Juncheng Dong, Weibin Mo, Zhengling Qi, Cong Shi, Ethan X. Fang, Vahid Tarokh, 2023, Proceedings of Machine Learning Research on p. 8276-8295

Most-Cited Papers

Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions

Mengdi Wang, Ethan X. Fang, Han Liu, 2017, Mathematical Programming on p. 419-449

Generalized alternating direction method of multipliers: new theoretical insights and applications

Ethan X. Fang, Bingsheng He, Han Liu, Xiaoming Yuan, 2015, Mathematical Programming Computation on p. 149-187

Accelerating Stochastic Composition Optimization

Mengdi Wang, Ji Liu, Ethan X. Fang, 2017, Journal of Machine Learning Research on p. 1-23

Testing and confidence intervals for high dimensional proportional hazards models

Ethan X. Fang, Yang Ning, Han Liu, 2017, Journal of the Royal Statistical Society. Series B: Statistical Methodology on p. 1415-1437

Adipocyte OGT governs diet-induced hyperphagia and obesity

Min Dian Li, Nicholas B. Vera, Yunfan Yang, Bichen Zhang, Weiming Ni, Enida Ziso-Qejvanaj, Sheng Ding, Kaisi Zhang, Ruonan Yin, Simeng Wang, Xu Zhou, Ethan X. Fang, Tian Xu, Derek M. Erion, Xiaoyong Yang, 2018, Nature Communications

Accelerating stochastic composition optimization

Mengdi Wang, Ji Liu, Ethan X. Fang, 2016, Advances in Neural Information Processing Systems on p. 1722-1730

Multilevel stochastic gradient methods for nested composition optimization

Shuoguang Yang, Mengdi Wang, Ethan X. Fang, 2019, SIAM Journal on Optimization on p. 616-659

Test of significance for high-dimensional longitudinal data

Ethan X. Fang, Yang Ning, Runze Li, 2020, Annals of Statistics on p. 2622-2645

IMPLICIT BIAS OF GRADIENT DESCENT BASED ADVERSARIAL TRAINING ON SEPARABLE DATA

Yan Li, Huan Xu, Tuo Zhao, Ethan X. Fang, 2020,

Max-norm optimization for robust matrix recovery

Ethan X. Fang, Han Liu, Kim Chuan Toh, Wen Xin Zhou, 2018, Mathematical Programming on p. 5-35