Survey details features for black-box optimization in machine learning

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-21 04:00

本调查论文详细介绍了用于表示单目标连续黑盒优化问题的特征。它涵盖了问题景观特征、算法特征和交互特征，借鉴了过去五年的最新研究。该论文旨在支持算法选择和配置等机器学习任务，并评估基准问题集的互补性。还讨论了局限性和未来的研究方向。 AI

影响为与优化问题中的机器学习相关的特征工程技术提供了结构化概述。

排序理由该条目是发表在 arXiv 上的调查论文，详细介绍了优化中机器学习应用的特征。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该条目是发表在 arXiv 上的调查论文，详细介绍了优化中机器学习应用的特征。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 51 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

arXiv cs.LG TIER_1 English(EN) · Gjorgjina Cenikj, Ana Nikolikj, Ga\v{s}per Petelin, Niki van Stein, Carola Doerr, Tome Eftimov · 2026-07-21 04:00

用于表示黑盒单目标连续优化的特征调查

arXiv:2406.06629v2 Announce Type: replace Abstract: This survey examines key advancements in designing features to represent optimization problem instances, algorithm instances, and their interactions within the context of single-objective continuous black-box optimization. These…