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News/Bayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods
arxiv
PublishedOctober 28, 2026 at 4:00 AM

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

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arXiv:2609.31107v2 Announce Type: replace 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 input space, which leads to an upper bound on the

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