High-Dimensional Partial Least Squares: Spectral Analysis and Fundamental Limitations

A new framework named GADPN has been proposed to enhance Graph Neural Networks (GNNs) by refining graph topology through low-rank denoising and generalized structural perturbation, addressing issues of noise and missing links in graph-structured data.

A recent study introduces the radius of statistical efficiency (RSE), a new measure that quantifies the robustness of estimation problems by determining the smallest perturbation that makes the Fisher information matrix singular. This research spans various statistical models, including principal component analysis and generalized linear models, highlighting the interplay between RSE and the complexity of these models.