Research Markets

Cost-Aware Stopping for Freeze-Thaw Bayesian Optimization: When Does One-Step Lookahead Suffice?

Oct 30, 2026 Source ↗

Key Insights

Freeze-thaw Bayesian optimization (BO) evaluates candidates in resumable increments but usually stops at a budget or convergence test.
We maximize a budget-free utility, the best observed score minus.

Beneficial Ownership Market Microstructure

Cite this synthesis DOI: 10.48550/arXiv.2610.42085 ↗

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@misc{ acaciamarkets-research-cost-aware-stopping-for-freeze-thaw-bayesian-optimization-wh,
  title = { Cost-Aware Stopping for Freeze-Thaw Bayesian Optimization: When Does One-Step Lookahead Suffice? },
  author = { Leszek },
  year = { 2026 },
  doi = { 10.48550/arXiv.2610.42085 },
  url = { http://arxiv.org/abs/2610.42085v1 },
  note = {Summarized and classified by AcaciaFund}
}

TY  - GEN
TI  - Cost-Aware Stopping for Freeze-Thaw Bayesian Optimization: When Does One-Step Lookahead Suffice?
AU  - Leszek
PY  - 2026
DO  - 10.48550/arXiv.2610.42085
UR  - http://arxiv.org/abs/2610.42085v1
ER  -

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Overview

Freeze-thaw Bayesian optimization (BO) evaluates candidates in resumable increments but usually stops at a budget or convergence test. We maximize a budget-free utility, the best observed score minus

Key Topics

Quantitative Modeling: A theme covered by this item within the markets context.

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market-microstructure quantitative-modeling

Beneficial Ownership Market Microstructure

SQI 0.750