| Date |
Presenter |
Title |
Wednesday, January 12
Time: 12:00-1:30 pm
Location: Online |
Reza Gheissari – University of California, Berkeley |
Gradient Methods for Parameter Estimation in High Dimensions |
Wednesday, January 19
Time: 12:00-1:30 pm
Location: Online |
Bianca Dumitrascu – University of Cambridge |
Statistical Machine Learning for Genetics and Health: Multi-modality, Interpretability, Mechanism |
Monday, January 24
Time: 12:00-1:30 pm
Location: Online |
Lihua Lei – Stanford University |
What Can Conformal Inference Offer to Statistics? |
Wednesday, January 26
Time: 12:00-1:30 pm
Location: Online |
Jiaoyang Huang – New York University |
Random Matrix Theory for Sparse Graphs and Statistical Learning |
Monday, January 31
Time: 12:00-1:30 pm
Location: Online |
Qi Lei – Princeton University |
Theoretical Foundations of Pretrained Models |
Wednesday, February 2
Time: 12:00-1:30 pm
Location: Online |
Mark Sellke – Stanford University |
Algorithmic Thresholds in Mean-Field Spin Glasses |
Monday, February 7
Time: 12:00-1:30 pm
Location: Online |
Feng Ruan – University of California, Berkeley |
Designing Better Nonconvex Models for Modern Statistical Applications |
Wednesday, February 9
Time: 12:00-1:30 pm
Location: Online |
Jason Altschuler – Massachusetts Institute of Technology |
Transport and Beyond: Efficient Optimization over Probability Distributions |
Monday, February 14
Time: 12:00-1:30 pm
Location: Online |
Alexander Wein – Georgia Institute of Technology |
Understanding Statistical-vs-Computational Tradeoffs via Low-Degree Polynomials |
Wednesday, February 16
Time: 12:00-1:30 pm
Location: Online |
Bingxin Zhao – Purdue University |
Biobank-scale Multi-organ Imaging Genetics: Clinical and Statistical Advances |
Monday, February 21
Time: 12:00-1:30 pm
Location: Online |
Nikolaos Ignatiadis – Stanford University |
Nonparametric Empirical Bayes Inference |
Wednesday, March 16
Time: 12:00-1:00 pm
Location: Online |
Rajen Shah – University of Cambridge |
Low-Priced Lunch in Conditional Independence Testing |
Wednesday, March 23
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Guanyang Wang – Rutgers University |
Unbiased Multilevel Monte Carlo Methods for Intractable Distributions: MLMC Meets MCMC |
Monday, March 28
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Osbert Bastani – University of Pennsylvania |
Statistical Guarantees for Trustworthy Deep Learning |
Wednesday, March 30
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Arun Kumar Kuchibhotla – Carnegie Mellon University |
Median Bias, HulC, and Valid Inference |
Wednesday, April 6
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Cynthia Rush – Columbia University |
On the Robustness of α-Posteriors to Model Misspecification |
Wednesday, April 13
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Désiré Kédagni – Iowa State University |
Marginal Treatment Effects with Misclassified Treatment |
Wednesday, April 20
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Jason Klusowski – Princeton University |
Large Scale Prediction with Decision Trees |
Thursday, April 21
Time: 12:00-1:00 pm
Location: G65 Jon M. Huntsman Hall |
Yingying Fan – University of Southern California |
Asymptotic Properties of High-Dimensional Random Forests |
Monday, April 25
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Rene Vidal – Johns Hopkins University |
Mathematics of Deep Learning: Global Optimality, Implicit Bias, and Learning Dynamics |
Wednesday, April 27
Time: 12:00-1:00 pm
Location: F55 Jon M. Huntsman Hall |
Andrew Nobel – University of North Carolina, Chapel Hill |
Stationary Optimal Transport with Applications to Graph Alignment |
