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Bayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods
Pulling back the Fisher metric yields a local sensitivity tensor that bounds acquisition gradients and explains high-dimensional BO failures, leading to the FITR trust-region method that replaces lengthscale heuristics with local Fisher weights.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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