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LIPO+: Frugal Global Optimization for Lipschitz Functions

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arxiv 2406.19723 v2 pith:YR7P36U5 submitted 2024-06-28 math.OC math.PR

classification math.OCmath.PR
keywords lipoalgorithmsfamilyfunctionsadalipobenchmarkcallcodes
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In this paper, we propose simple yet effective empirical improvements to the algorithms of the LIPO family, introduced in [Malherbe2017], that we call LIPO+ and AdaLIPO+. We compare our methods to the vanilla versions of the algorithms over standard benchmark functions and show that they converge significantly faster. Finally, we show that the LIPO family is very prone to the curse of dimensionality and tends quickly to Pure Random Search when the dimension increases. We give a proof for this, which is also formalized in Lean mathematical language. Source codes and a demo are provided online.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants

    cs.LG 2025-02 conditional novelty 7.0 of 10

    ECP is a no-regret global optimization algorithm for Lipschitz black-box functions with unknown constant, achieving minimax-optimal regret via an expanding acceptance region.

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