A new paper explores the impact of feature computation budgets on per-instance algorithm selection (PIAS) for black-box optimization. The study investigates how much of the optimization budget should be allocated to computing instance features for PIAS to be beneficial. Findings indicate that PIAS remains viable even when a significant portion of the budget is used for feature computation, though the optimal tradeoff varies by scenario. AI
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IMPACT This research could inform the design of more efficient optimization algorithms by clarifying the trade-offs in feature computation.
RANK_REASON This is a research paper published on arXiv discussing a specific technical aspect of optimization algorithms.