Emerging Data Science Methods for Complex Data with Endogeneity and/or Heterogeneity

Organizing committee: Xuming He (University of Michigan), Kengo Kato (Cornell University), Snigdha Panigrahi  (University of Michigan), Lan Wang (University of Miami), Qi Zheng (University of Louisville)

This is part of the activities of our NSF-funded Focused Research Group (FRG: Collaborative Research: Quantile-Based Modeling for Large-Scale Heterogeneous Data) activities.

This project is part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity.

Lan Wang, Bo Peng, Jelena Bradic, Runze Li and Yunan Wu. (2020) A tuning-free robust and efficient  approach to high-dimensional regression. Journal of the American Statistical Association, 115, 1700-1714.

 Our invited talk slides for JSM 2020

Discussions from Professors. Jianqing Fan , Cong Ma & Kaizheng Wang 

Discussions from Professor Po-Ling Loh

Discussion from Professors Xiudi Li & Ali Shojaie 

Authors' rejoinder

Winter Research Conference on Machine Learning and Business, University of Miami, 2021.