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CAP: Learning to Optimize from Sparse Observations of Related Tasks

arXiv cs.LG ↗ · 2026-11-02 Cached

The paper proposes CAP (Candidate Acquisition Policy), a method that learns a feedback-conditioned query policy from sparse records of related black-box optimization tasks, achieving the best final-budget results on four synthetic families and two engineering benchmarks (BOPTEST, SU2).

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