2020
Student Seminar: Chen Xu
11:30 am–12:00 pm via ZOOM
Master’s Thesis Presentation
CHEN XU, Department of Statistics, The University of Chicago
“Efficient Predictive Inference with Jackknife+ under Ensemble Learning”
Statistics Colloquium: Eric Jonas
4:00–5:00 pm Via ZOOM
ERIC JONAS, Department of Computer Science, University of Chicago
“Machine Learning for Molecular Inverse Problems”
Student Seminar: Youngseok Kim
3:00–4:30 pm Via ZOOM
Dissertation Presentation and Defense
YOUNGSEOK KIM, Department of Statistics, The University of Chicago
“Bayesian Shrinkage Methods for High-dimensional Regression”
Student Seminar: Blaine Cole
1:00–1:30 pm Via ZOOM
Master’s Thesis Presentation,
Blaine Cole, Department of Statistics, The University of Chicago
“Unsupervised Domain Adaptation through Paired Unlabeled Data”
Student Seminar: Zeyu Hu
10:30–11:00 am Via ZOOM
Master’s Thesis Presentation
ZEYU HU, Department of Statistics, The University of Chicago
“Kernel Estimation of Conditional Quantile for Value at Risk”
Student Seminar: Yanfei Zhou
3:00–3:30 pm Via ZOOM
Master’s Thesis Presentation
YANFEI ZHOU, Department of Statistics, The University of Chicago
“An Empirical Study of a Fully Online Approach for Statistical Inference Based on SGD”
Student Seminar: Changji Xu
3:00–4:30 pm Via ZOOM
Dissertation Presentation and Defense
CHANGJI XU, Department of Statistics, The University of Chicago
“Random Walk Among Bernoulli Obstacles”
Student Seminar: Petr Panov
1:30–3:00 pm Via ZOOM
Dissertation Presentation and Defense
PETR PANOV, Department of Statistics, The University of Chicago
“Loop Soup Occupation Fields and Poisson Cylinders”
Student Seminar: Yi-Hung Liu
1:00–1:30 pm Via ZOOM
Master’s Thesis Presentation
YI-HUNG LIU, Department of Statistics, The University of Chicago
“Causal Relations and Feature Extraction in Contextualized Sentence Representation”
Statistics Colloquium: Bryon Aragam
4:00–5:00 pm Via ZOOM
BRYON ARAGAM, Booth School of Business at the University of Chicago
“Identifiability of Nonparametric Mixture Models, Clustering, and Semi-supervised Learning”