Generalized alternating direction method of multipliers: new theoretical insights and applications. - Ethan X. Fang; Bingsheng He; Han Liu 001; Xiaoming Yuan 001 (Math. Program. Comput., 2015)

Misspecified Nonconvex Statistical Optimization for Phase Retrieval. - Zhuoran Yang; Lin F. Yang; Ethan X. Fang; Tuo Zhao; Zhaoran Wang 001; Matey Neykov (CoRR, 2017)

Accelerating Stochastic Composition Optimization. - Mengdi Wang; Ji Liu; Ethan X. Fang (J. Mach. Learn. Res., 2017)

Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions. - Mengdi Wang; Ethan X. Fang; Han Liu 001 (Math. Program., 2017)

Max-norm optimization for robust matrix recovery. - Ethan X. Fang; Han Liu 001; Kim-Chuan Toh; Wen-Xin Zhou (Math. Program., 2018)

Inductive Bias of Gradient Descent based Adversarial Training on Separable Data. - Yan Li 074; Ethan X. Fang; Huan Xu; Tuo Zhao (CoRR, 2019)

Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach. - Ethan X. Fang; Han Liu 001; Mengdi Wang (Math. Program., 2019)

Misspecified nonconvex statistical optimization for sparse phase retrieval. - Zhuoran Yang; Lin F. Yang; Ethan X. Fang; Tuo Zhao; Zhaoran Wang 001; Matey Neykov (Math. Program., 2019)

Multilevel Stochastic Gradient Methods for Nested Composition Optimization. - Shuoguang Yang; Mengdi Wang; Ethan X. Fang (SIAM J. Optim., 2019)

Implicit Bias of Gradient Descent based Adversarial Training on Separable Data. - Yan Li 074; Ethan X. Fang; Huan Xu; Tuo Zhao (ICLR, 2020)

Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection. - Yining Wang; Yi Chen; Ethan X. Fang; Zhaoran Wang 001; Runze Li (CoRR, 2020)

Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy. - Han Zhong 001; Ethan X. Fang; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2020)

High-Dimensional Interactions Detection with Sparse Principal Hessian Matrix. - Cheng Yong Tang; Ethan X. Fang; Yuexiao Dong (J. Mach. Learn. Res., 2020)

Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data. - Yan Li 074; Caleb Ju; Ethan X. Fang; Tuo Zhao (CoRR, 2021)

Stochastic Compositional Optimization with Compositional Constraints. - Shuoguang Yang; Zhe Zhang; Ethan X. Fang (CoRR, 2022)

PASTA: Pessimistic Assortment Optimization. - Juncheng Dong; Weibin Mo; Zhengling Qi; Cong Shi 001; Ethan X. Fang; Vahid Tarokh (ICML, 2023)

Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games. - Zihan Zhu; Ethan X. Fang; Zhuoran Yang (NeurIPS, 2023)

Combinatorial Inference on the Optimal Assortment in the Multinomial Logit Model. - Shuting Shen; Xi Chen 010; Ethan X. Fang; Junwei Lu (EC, 2023)

Inference on the Optimal Assortment in the Multinomial Logit Model. - Shuting Shen; Xi Chen; Ethan X. Fang; Junwei Lu (CoRR, 2023)

Pivotal Estimation of Linear Discriminant Analysis in High Dimensions. - Ethan X. Fang; Yajun Mei; Yuyang Shi; Qunzhi Xu; Tuo Zhao (J. Mach. Learn. Res., 2023)

Lagrangian Inference for Ranking Problems. - Yue Liu; Ethan X. Fang; Junwei Lu (Oper. Res., 2023)

Robust matrix estimations meet Frank-Wolfe algorithm. - Naimin Jing; Ethan X. Fang; Cheng Yong Tang (Mach. Learn., 2023)

Ranking of Large Language Model with Nonparametric Prompts. - Zebin Wang; Yi Han 008; Ethan X. Fang; Lan Wang; Junwei Lu (CoRR, 2024)

Data-Driven Compositional Optimization in Misspecified Regimes. - Shuoguang Yang; Ethan X. Fang; Uday V. Shanbhag (Oper. Res., 2025)

Offline Feature-Based Pricing Under Censored Demand: A Causal Inference Approach. - Jingwen Tang; Zhengling Qi; Ethan X. Fang; Cong Shi 001 (Manuf. Serv. Oper. Manag., 2025)

Contextual Online Uncertainty-Aware Preference Learning for Human Feedback. - Nan Lu; Ethan X. Fang; Junwei Lu (CoRR, 2025)

A Smoothed Augmented Lagrangian Framework for Convex Optimization with Nonsmooth Constraints. - Peixuan Zhang; Uday V. Shanbhag; Ethan X. Fang (J. Sci. Comput., 2025)