Starting January 24th, the OTMLE (Optimal Transport and Targeted Maximum Likelihood Estimation) reading group will further investigate the geometry of probability spaces and the implications for TMLE’s structure and behavior. Topics include deeper explorations of how optimal transport’s spatial and dynamic properties provide insights into likelihood-based optimization and its role in semiparametric models. Rather than diving into specific optimization techniques like natural gradient descent or Newton’s method, this semester focuses on laying the theoretical groundwork for...
