Bayesian Optimization with Rich Auxiliary Information via LLMs
Two methods are introduced, AuxBO-Evolve, which uses auxiliary information to evolve beliefs over the location of the optimum, and AuxBO-Vicinity, which uses it to locally guide the acquisition function, which consistently improve optimization performance and outperform standard BO and existing LLM-based approaches.
Efe Mert Karagözlü, Rohit Sonker, Tejus Gupta et al.
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