# Versatile Black-Box Optimization

arXiv: https://arxiv.org/abs/2004.14014 · HTML: https://mlsanity.com/paper/2004.14014/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Apr 2020.

## Built on by (most cited first, 22 of 22)

- [Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey](https://mlsanity.com/paper/2403.14608/) (2024)
- [LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition](https://mlsanity.com/paper/2307.13269/) (2023)
- [AdaMerging: Adaptive Model Merging for Multi-Task Learning](https://mlsanity.com/paper/2310.02575/) (2023)
- [Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment](https://mlsanity.com/paper/2312.12148/) (2023)
- [Parameter Efficient Multi-task Model Fusion with Partial Linearization](https://mlsanity.com/paper/2310.04742/) (2023)
- [LM-Cocktail: Resilient Tuning of Language Models via Model Merging](https://mlsanity.com/paper/2311.13534/) (2023)
- [Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent](https://mlsanity.com/paper/2501.01230/) (2025)
- [Model-Based Diffusion for Trajectory Optimization](https://mlsanity.com/paper/2407.01573/) (2024)
- [ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization](https://mlsanity.com/paper/2311.13171/) (2023)
- [StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements](https://mlsanity.com/paper/2408.15666/) (2024)
- [Generating Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution](https://mlsanity.com/paper/2108.01077/) (2021)
- [On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion](https://mlsanity.com/paper/2406.15480/) (2024)
- [Divide, Reweight, and Conquer: A Logit Arithmetic Approach for In-Context Learning](https://mlsanity.com/paper/2410.10074/) (2024)
- [Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization](https://mlsanity.com/paper/2203.13968/) (2022)
- [Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies](https://mlsanity.com/paper/2205.01324/) (2022)
- [Generating 2D and 3D Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution](https://mlsanity.com/paper/2211.13964/) (2022)
- [Evolutionary Retrofitting](https://mlsanity.com/paper/2410.11330/) (2024)
- [Exploiting Function-Family Structure in Analog Circuit Optimization](https://mlsanity.com/paper/2512.00712/) (2025)
- [Do the Frankenstein, or how to achieve better out-of-distribution performance with manifold mixing model soup](https://mlsanity.com/paper/2309.08610/) (2023)
- [Log-normal Mutations and their Use in Detecting Surreptitious Fake Images](https://mlsanity.com/paper/2409.15119/) (2024)
- [MedForge: Building Medical Foundation Models Like Open Source Software Development](https://mlsanity.com/paper/2502.16055/) (2025)
- [OPTION: OPTImization Algorithm Benchmarking ONtology](https://mlsanity.com/paper/2211.11332/) (2022)

## Abstract (arXiv)

Choosing automatically the right algorithm using problem descriptors is a classical component of combinatorial optimization. It is also a good tool for making evolutionary algorithms fast, robust and versatile. We present Shiwa, an algorithm good at both discrete and continuous, noisy and noise-free, sequential and parallel, black-box optimization. Our algorithm is experimentally compared to competitors on YABBOB, a BBOB comparable testbed, and on some variants of it, and then validated on several real world testbeds.