Utilitarian Algorithm Configuration for Infinite Parameter Spaces
Not on the map. Why?
Abstract (arXiv)
Utilitarian algorithm configuration is a general-purpose technique for automatically searching the parameter space of a given algorithm to optimize its performance, as measured by a given utility function, on a given set of inputs. Recently introduced utilitarian configuration procedures offer optimality guarantees about the returned parameterization while provably adapting to the hardness of the underlying problem. However, the applicability of these approaches is severely limited by the fact that they only search a finite, relatively small set of parameters. They cannot effectively search the configuration space of algorithms with continuous or uncountable parameters. In this paper we introduce a new procedure, which we dub COUP (Continuous, Optimistic Utilitarian Procrastination). COUP is designed to search infinite parameter spaces efficiently to find good configurations quickly. Furthermore, COUP maintains the theoretical benefits of previous utilitarian configuration procedures when applied to finite parameter spaces but is significantly faster, both provably and experimentally.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 21 references that are in the map. First posted on arXiv 28 May 2024.
Builds on
9 of 21 references.
References · 9
- 2016Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimizationcited by 688
- 2015Non-stochastic Best Arm Identification and Hyperparameter Optimizationcited by 219
- 2015A PAC Approach to Application-Specific Algorithm Selectioncited by 57
- 2016Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problemscited by 30
- 2018LeapsAndBounds: A Method for Approximately Optimal Algorithm Configurationcited by 13
- 2019Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configurationcited by 9
- 2022AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configurationcited by 6
- 2022Formalizing Preferences Over Runtime Distributionscited by 2
- 2023Utilitarian Algorithm Configurationcited by 1
Built on by
Citing papers per year: 2025: 1; 2026: 1.
2 papers.
- 2026QuickScope: Certifying Hard Questions in Dynamic LLM Benchmarkscited by 1
- 2025Practical, Utilitarian Algorithm Configurationcited by 0
- 2026QuickScope: Certifying Hard Questions in Dynamic LLM Benchmarks20 Apr 2026
- 2025Practical, Utilitarian Algorithm Configuration16 Oct 2025