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SMAC TALKS FALL 2023
Stochastic Modeling and Computational Statistics
Stochastic Modeling and Computational Statistics
Fall 2023
SMAC talks are held each Friday during fall and spring semesters from 10:10 AM to 11:00 AM in 327 Thomas Building and on Zoom. Talks last 40 minutes, with time for clarification questions. The last 10 minutes are for open-ended discussion.
The general guidelines for each talk:
- 40 minutes for each talk + 10 minutes for discussion.
- The talk should be accessible to all grad students who have completed 1 year of the program.
- Informal style. For instance, chalk and blackboard talks are welcome.
- Interruptions during the talk are welcome but they should only be for clarifications; longer questions are to be left to the discussion period.
- Unpublished work may not be shared or discussed outside the group without the permission of the speaker/author.
- While a large proportion of the talks may be related to stochastic modeling and computing, a much broader list of topics have also been discussed in this series.
Date | Speaker | Title |
---|---|---|
9/1/23 | Anirudh Subramanyam | Optimization with Rare Events |
9/8/23 | Stephen Berg | Statistical and computational aspects of shape-constrained inference for covariance function estimation |
9/15/23 | Jingyuan Liu | A Generalized Knockoff Procedure for FDR Control in Structural Change Detection |
9/22/23 | Omar Hagrass | Spectral Regularized Kernel Goodness-of-Fit Tests |
9/29/23 | Jacopo Iorio | Two new biclustering-inspired FDA methods. |
10/6/23 | Wei Zhong | Estimation and Inference for Multi-Kink Quantile Regression |
10/13/23 | Murali Haran | The Intractable Normalizing Function Problem |
10/27/23 | Cornelius Fritz | A Scalable Statistical Platform for Learning from Discrete and Dependent Attribute and Network Data Generalizing GLMs |
11/10/23 | Satarupa Bhattacharjee | Geodesic Mixed Effects Models for Repeatedly Observed/Longitudinal Random Objects |
11/17/23 | Benjamin Roycraft | Feature Generating Models: Inference in Purely High Dimensions |
A look back at previous SMAC TALKS.