Direct Debiased Machine Learning via Bregman Divergence Minimization
PositiveArtificial Intelligence
A new framework for direct debiased machine learning has been introduced, combining Neyman targeted estimation with generalized Riesz regression. This innovative approach not only streamlines the process of debiasing in machine learning but also enhances covariate balancing and targeted maximum likelihood estimation. By addressing the complexities of causal effects and structural models, this framework promises to improve the accuracy of regression functions, making it a significant advancement in the field of machine learning.
— Curated by the World Pulse Now AI Editorial System
