Bayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods.

arXiv:2609.31107v2 Announce Type: replace-cross Abstract: We study Bayesian optimization (BO) through the lens of information geometry. Pulling back the Fisher information metric through the surrogate posterior map yields a local sensitivity tensor on the inpu