# LIPO+: Frugal Global Optimization for Lipschitz Functions

arXiv: https://arxiv.org/abs/2406.19723 · HTML: https://mlsanity.com/paper/2406.19723/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jun 2024.

## Built on by (most cited first, 2 of 2)

- [Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants](https://mlsanity.com/paper/2502.04290/) (2025)
- [ECPv2: Fast, Efficient, and Scalable Global Optimization of Lipschitz Functions](https://mlsanity.com/paper/2511.16575/) (2025)

## Abstract (arXiv)

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.