Graduate Student Seminar.
The Grad Seminar is a presentation series arranged by and for graduate students at GW, where students will take turn to deliver talks. These talks may cover a broad spectrum of subjects and are not necessarily limited to the one's own research. This seminar seeks to foster a casual environment in which graduate students can acquire skills in delivering technical presentations and get exposed to new challenges in statistics/mathematics.
The following are the presentation topic/slides of previous speakers (not necessarily from Hu's group).
Double-debiased machine learning for treatment and structural parameters (Speaker: Zixuan Zhao, 11.10.2023).
High dimensional Classification and clustering with feature selection (Speaker: Yong Wang, 11.17.2023).
A benchmark and comparison of active learning for logistic regression (Speaker: Yi Zhang, 12.8.2023).
Smoothed quantile regression for analyzing spatial data over complex domains (Speaker: Jilei Lin, 1.26.2024).
Causal inference under network interference (Speaker: Zexin Ren, 2.2.2024).
Bayesian Iterative Prediction and Lexical-based Interpretation for Disturbed Chinese Sentence Pair Matching (Speaker: Muzhe Guo, 2.16.2024)
Subgroup Analyses in clinical trials based on The Desirability of Outcome Ranking (Speaker:Weixiao Dai, 3.1.2024).
A review of rerandomization method and comparison (Speaker: Ziji Qin, 3.29.2024).
High-dimensional Extreme Quantile Regression (Speaker: Yiwei Tang, 4.12.2024).
Gradient Descent Methods on Riemannian Manifolds and Their Applications in Weighted Low Rank Approximation Problem (Conglong Xu, 4.19.2024, GWU Math dept).
Empirical process reading group (Planned 2024 fall).
We are interested in the theory of empirical process and its applications. We will mainly follow the following references:
A gentle introduction to empirical process theory and applications by Bodhisattva Sen.
Introduction to Empirical Processes and Semiparametric Inference by Michael R. Kosorok.
Weak convergence and Empirical Processes with applications to statistics by Aad W. van der Vaart and Jon A. Wellner.
The reading group will be arranged in person and typed notes/slides will be uploaded on a timely basis. Timetable
Notes/Slides: