2022
CAM Colloquium: Fabian Faulstich
4:00–5:00 pm Jones 303
FABIAN FAULSTICH, Department of Mathematics, University of California, Berkeley
“On the Pure State V-representability of Density Matrix Embedding Theory”
Statistics Colloquium: Mladen Kolar
4:30–5:30 pm Jones 303
MLADEN KOLAR, Econometrics and Statistics, University of Chicago Booth School of Business
“Adaptive Stochastic Optimization with Constraints”
CAM Colloquium: Adriana Gillman
4:00–5:00 pm Jones 303
ADRIANA GILLMAN, Department of Applied Mathematics, University of Colorado, Boulder
“Fast Direct Solvers for Boundary Integral Equations”
Student Seminar: Cheng Peng
2:00–2:30 pm Via Zoom
Master’s Thesis Presentation
CHENG PENG, Department of Statistics, The University of Chicago
“LASSO-Driven Simultaneous Inference on High Dimensional Dependent Data”
Student Seminar: Joonsuk Kang
1:30–3:00 pm Jones 304
Dissertation Proposal Presentation
JOONSUK KANG, Department of Statistics, The University of Chicago
“Learning Meaningful Representations of Data with Empirical Bayes Methods”
Statistics Colloquium: Will Fithian
4:30–5:30 pm Jones 303
WILL FITHIAN, Department of Statistics, University of California, Berkeley
“Conditional calibration: controlling FDR under dependence, uniformly improving knockoffs, and estimating model selection FDR”
DSI Autumn 2022 Distinguished Speaker Series: Jordan Boyd-Graber
12:00–1:30 pm JCL 390
This talk will also be broadcast via Zoom. Please register to receive viewing information.
JORDAN BOYD-GRABER, University of Maryland
“If We Want AI to be Interpretable, We Need to Define and Measure It”
CAM Colloquium: Benjamin Recht
4:00–5:00 pm Jones 303
BENJAMIN RECHT, Department of Electrical Engineering and Computer Science, University of California, Berkeley
“Steampunk Data Science”
Student Seminar: Weishi Wang
2:00–2:30 pm Jones 303
Master’s Thesis Presentation
WEISHI WANG, Department of Statistics, The University of Chicago
“GAN-MC: a Variance Reduction Tool for Derivatives Pricing”
Statistics Colloquium: Kathryn Roeder
4:30–5:30 pm Jones 303
KATHRYN ROEDER, Department of Statistics, Carnegie Mellon University
“Model-free prediction test and distribution-free independence test for high dimension data with applications to genomics data”