Ethan Xingyuang Fang
Assistant Professor of Statistics
-
421B Thomas
University Park, PA - xxf13@psu.edu
- 814-865-3235
Links
Publication Tags
Optimization Chemical Analysis Randomized Trial Confidence Interval Gradient Methods Estimator Linear Programming High Dimensional Testing Optimization Problem Gradient Method Test Statistic Stochastic Gradient Stochastic Methods O Glcnac Transferase Proportional Hazards Model Fats Hypothesis Testing Recovery Obesity Hazard Function Longitudinal Data Statistics Experiments Type I ErrorMost Recent Papers
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
Optimal, two-stage, adaptive enrichment designs for randomized trials, using sparse linear programming
Michael Rosenblum, Ethan X. Fang, Han Liu, 2020, Journal of the Royal Statistical Society. Series B: Statistical Methodology on p. 749-772
Test of significance for high-dimensional longitudinal data
Ethan X. Fang, Yang Ning, Runze Li, 2020, Annals of Statistics on p. 2622-2645
High-dimensional interactions detection with sparse principal hessian matrix
Cheng Yong Tang, Ethan X. Fang, Yuexiao Dong, 2020, Journal of Machine Learning Research
Constructing a confidence interval for the fraction who benefit from treatment, using randomized trial data
Emily J. Huang, Ethan X. Fang, Daniel F. Hanley, Michael Rosenblum, 2019, Biometrics on p. 1228-1239
Misspecified nonconvex statistical optimization for sparse phase retrieval
Zhuoran Yang, Lin F. Yang, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov, 2019, Mathematical Programming on p. 545-571
Blessing of massive scale: Spatial graphical model estimation with a total cardinality constraint approach
Xingyuan Fang, Han Liu, Mengdi Wang, 2019, Mathematical Programming on p. 175-205
Multilevel stochastic gradient methods for nested composition optimization
Shuoguang Yang, Mengdi Wang, Ethan X. Fang, 2019, SIAM Journal on Optimization on p. 616-659
Adipocyte OGT Regulates a Fat-Sensing Adipose-to-Brain Axis That Induces Hyperphagia and Obesity
Min-Dian Li, N Vera, Y Yang, B Zhang, W Ni, E Ziso-Qejvanaj, S Ding, K Zhang, R Yin, S Wang, X Zhou, Xingyuan Fang, T Xu, E Erion, Xiaoyong Yang, 2018, Nature Communications
Most-Cited Papers
Stochastic compositional gradient descent
Mengdi Wang, Ethan X. Fang, Han Liu, 2017, Mathematical Programming on p. 419-449
Generalized alternating direction method of multipliers
Xingyuan 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, 2016, Advances in Neural Information Processing Systems on p. 1722-1730
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
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
Inequality in treatment benefits
Emily J. Huang, Ethan X. Fang, Daniel F. Hanley, Michael Rosenblum, 2017, Biostatistics on p. 308-324
Accelerating Stochastic Composition Optimization
Mengdi Wang, Ji Liu, Ethan X. Fang, 2017, Journal of Machine Learning Research on p. 1-23
Using a distributed SDP approach to solve simulated protein molecular conformation problems
Xingyuan Fang, Kim Chuan Toh, 2013, on p. 351-376
Multilevel stochastic gradient methods for nested composition optimization
Shuoguang Yang, Mengdi Wang, Ethan X. Fang, 2019, SIAM Journal on Optimization on p. 616-659
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