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Evidence record 5919 · automatically gathered

BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH

Bayesian optimization (BO) has for sequential optimization of expensive black-box functions demonstrated practicality and effectiveness in many real-world settings. Meta-Bayesian optimization (meta-BO) focuses on improving the sample efficiency of BO by making use of information from related tasks. Although meta-BO is sample-efficient when task structure transfers, poor alignment between meta-training and test tasks can cause suboptimal queries to be suggested during online optimization. To this

Record details

Published: 13 April 2026
Source: arXiv
Category: Research
Topics: Safety & alignment
Retrieved: 14 July 2026

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How to cite this record

ethics.ai (13 April 2026), “BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH,” evidence record 5919, https://ethics.ai/record/5919 (originally published by arXiv).

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