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English(EN) Graph Instance Landscapes: When Structural Similarity Does (Not) Reflect Shortest-Path Performance

新方法分析图结构以评估最短路径算法

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种通过分析图结构来评估最短路径算法的新方法。该方法将图嵌入到特征空间并进行聚类，以识别结构相似的区域，然后用这些区域来评估算法性能。研究考察了Erdos-Renyi图、随机几何图和道路网络，并测试了Dijkstra、双向Dijkstra和A*等算法。研究结果表明，虽然图生成器会创建稳定的结构区域，但性能相似性并不总是与结构相似性一致，并且不同的基准测试族占据不同的区域。 AI

排序理由 该集群包含一篇详细介绍新算法基准测试方法的论文。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.LG 阅读 →

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新方法分析图结构以评估最短路径算法

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该集群包含一篇详细介绍新算法基准测试方法的论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Maryam Gholami Shiri, Ivana Krminac, Marko Djukanovi\'c, Sa\v{s}o D\v{z}eroski, Eva Tuba, Tome Eftimov ·

    图实例景观：结构相似性何时（不）反映最短路径性能

    arXiv:2606.18267v1 Announce Type: cross Abstract: Benchmarking shortest-path algorithms is commonly based on aggregate performance over heterogeneous graph sets, which limits insight into how different search paradigms react to instance structure. We adopt an instance-landscape v…

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