2023
Computer Science Seminar: Amy Greenwald
11:00 am–12:00 pm Location TBA
Amy Greenwald, Brown University
“From Min-max Optimization to Stackelberg Games: Solutions and Applications”
Autumn 2023 Distinguished Speaker Series: Adam Klivans
12:00–1:30 pm John Crerar Library, Room 390
Presented by the Data Science Institute in partnership with the Departments of Statistics, Computer Science, and the Committee on Computational and Applied Mathematics
Adam Klivans, Department of Computer Science, University of Texas at Austin
“Testable Learning”
CAM Colloquium: Mathias Oster
4:00–5:00 pm Jones 303
Mathias Oster, Institute für Geometrie und Praktische Mathematik at the RWTH Aachen
“On Semi-global Optimal Control and its Application to Machine Learning”
Student Seminar: Yu-Wei Chen
10:30–11:00 am Jones 304
Wednesday, October 11, 2023, at 10:30 AM, in Jones 304, 5747 S. Ellis Avenue
Master’s Thesis Presentation
Yu-Wei Chen, Department of Statistics, The University of Chicago
“User-Based Batch Sampling for Bayesian Personalized Ranking with Matrix Factorization (BPR-MF)”
AI+Science Initiative Speaker Series: Maryellen L. Giger
4:30–6:00 pm William Eckhardt Research Center, Room 401
Maryellen L. Giger, A.N. Pritzker Distinguished Service Professor of Radiology, Committee on Medical Physics, at the University of Chicago
“AI in Medical Imaging and the Role of MIDRC”
CAM & Stats Student Seminar: Jiaheng Chen
12:30–1:30 pm Jones 303
JIAHENG CHEN, Committee on Computational and Applied Mathematics, University of Chicago
“Covariance Operator Estimation in the Small Lengthscale Regime”
Statistics Colloquium: Sabyasachi Chatterjee
11:30 am–12:30 pm Jones 303
Sabyasachi Chatterjee, Department of Statistics, University of Illinois Urbana-Champaign
“Theory for Cross Validation in Nonparametric Regression”
Autumn 2023 Distinguished Speaker Series: Maryam Fazel
12:00–1:30 pm JCL 390
Presented by the Data Science Institute in partnership with the Departments of Statistics, Computer Science, and the Committee on Computational and Applied Mathematics
Maryam Fazel, Moorthy Family Professor of Electrical and Computer Engineering at the University of Washington
“Flat Minima and Generalization in Learning: the Case of Low-rank Matrix Recovery”
CAM Colloquium: Anna Seigal
4:00–5:00 pm Jones 303
Anna Seigal, School of Engineering and Applied Sciences, Harvard University
“Factorising data”
Big Data and Machine Learning in Econometrics, Finance, and Statistics
Through October 7, 2023 Eckhardt Research Center, Room 161
This conference is made possible by the generous philanthropy of University of Chicago Trustee Steve G. Stevanovich and the Financial Mathematics Program.