Current Programs (2019-20)
1) Games, Decisions, Risk and Reliability (GDRR)
- This program will include game theory and adversarial risk analysis topics, relate these to decision theory, and also apply decision theory to risk analysis. An exciting aspect of the program will be to address non-standard utility functions that take account of the cost of memory, computation, and human effort to set up the analysis—these considerations are directly relevant to issues that arise in machine learning and data science. GDRR is the only year-long program in 2019-2020.
2) Deep Learning (DL)
- Deep Learning will be presented in the fall semester of 2019. The program will focus on statistical strategies for improving machine learning. There is vast interest in automated methods for complex data analysis. However, there is a lack of consideration of: (1) interpretability; (2) uncertainty quantification; (3) applications with limited training data; and (4) selection bias. Statistical methods can achieve (1)-(4) through a change in focus.
- Causal Inference will be presented in the spring semester of 2020. Medical and health applications will be a significant theme, but other applications will be considered. Much of the new work in causal inference entails modern machine learning tools, and this perspective will be important to the program.
Upcoming Programs (2020-21)
- July 14, 2019 – July 24, 2019 Industrial Math/Stat Modeling Workshop for Graduate Students
The Statistical and Applied Mathematical Sciences Institute (SAMSI) invites proposals for year-long research programs, workshops and shorter summer programs.
SAMSI organizes numerous workshops, scientific and educational. Application forms can be found on the pages of the individual workshops.