Search Results - "Fang, Ethan X."

Data-Driven Compositional Optimization in Misspecified Regimes.

Authors: Yang, Shuoguang Fang, Ethan X. Shanbhag, Uday V.

Source: Operations Research. May/Jun2025, Vol. 73 Issue 3, p1395-1411. 17p.

Robust matrix estimations meet Frank–Wolfe algorithm.

Authors: Jing, Naimin Fang, Ethan X. Tang, Cheng Yong

Source: Machine Learning; Jul2023, Vol. 112 Issue 7, p2723-2760, 38p

A Smoothed Augmented Lagrangian Framework for Convex Optimization with Nonsmooth Constraints.

Authors: Zhang, Peixuan Shanbhag, Uday V. Fang, Ethan X.

Source: Journal of Scientific Computing; Aug2025, Vol. 104 Issue 2, p1-43, 43p

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

Authors: Rosenblum, Michael Fang, Ethan X. Liu, Han

Source: Journal of the Royal Statistical Society: Series B (Statistical Methodology); Jul2020, Vol. 82 Issue 3, p749-772, 24p

Combinatorial Inference on the Optimal Assortment in the Multinomial Logit Model.

Authors: Shen, Shuting Chen, Xi Fang, Ethan X. et al.

Source: EC: Economics & Computation; 2023, p1080-1080, 1p

Lagrangian Inference for Ranking Problems.

Authors: Liu, Yue Fang, Ethan X. Lu, Junwei

Source: Operations Research. Jan/Feb2023, Vol. 71 Issue 1, p202-223. 22p. 4 Charts, 6 Graphs.

Constructing a confidence interval for the fraction who benefit from treatment, using randomized trial data.

Authors: Huang, Emily J. Fang, Ethan X. Hanley, Daniel F. et al.

Source: Biometrics; Dec2019, Vol. 75 Issue 4, p1228-1239, 12p

Stochastic Compositional Optimization with Compositional Constraints.

Authors: Yang, Shuoguang You, Wei Zhang, Zhe et al.

Source: INFORMS Journal on Optimization. Winter2026, Vol. 8 Issue 1, p1-21. 21p.

Fairness-Oriented Learning for Optimal Individualized Treatment Rules.

Authors: Fang, Ethan X. Wang, Zhaoran Wang, Lan

Source: Journal of the American Statistical Association. Sep2023, Vol. 118 Issue 543, p1733-1746. 14p.

Misspecified nonconvex statistical optimization for sparse phase retrieval.

Authors: Yang, Zhuoran Yang, Lin F. Fang, Ethan X. et al.

Source: Mathematical Programming; Jul2019, Vol. 176 Issue 1/2, p545-571, 27p

Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach.

Authors: Fang, Ethan X. Liu, Han Wang, Mengdi

Source: Mathematical Programming; Jul2019, Vol. 176 Issue 1/2, p175-205, 31p

Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection.

Authors: Chen, Yi Wang, Yining Fang, Ethan X. et al.

Source: Journal of the American Statistical Association. Mar2024, Vol. 119 Issue 545, p246-258. 13p.

Mining Massive Amounts of Genomic Data: A Semiparametric Topic Modeling Approach.

Authors: Fang, Ethan X. Li, Min-Dian Jordan, Michael I. et al.

Source: Journal of the American Statistical Association. Sep2017, Vol. 112 Issue 519, p921-932. 12p.

Deep Spatial Q-Learning for Infectious Disease Control.

Authors: Liu, Zhishuai Clifton, Jesse Laber, Eric B. et al.

Source: Journal of Agricultural, Biological & Environmental Statistics (JABES). Dec2023, Vol. 28 Issue 4, p749-773. 25p.

A Generative Adversarial Network Approach to Calibration of Local Stochastic Volatility Models.

Authors: Cuchiero, Christa Khosrawi, Wahid Teichmann, Josef

Source: Risks. Dec2020, Vol. 8 Issue 4, p101. 1p.