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English(EN) Is the Statistical Advantage Worth the Cost? An Empirical Comparison of KANs and MLPs for Structured Data Classification

KANs在结构化数据上优于MLPs，但计算成本更高

作者 PulseAugur 编辑部 · [3 个来源] ·

arXiv上发表的一项新研究将Kolmogorov-Arnold网络（KANs）与传统的Multi-Layer Perceptrons（MLPs）在结构化数据分类任务上进行了比较。研究发现，KANs在二分类和多分类数据集上统计上优于MLPs，提供了显著的总体优势。然而，这种改进的泛化能力是以参数和计算复杂度显著增加为代价的，这表明在资源受限的环境中，MLPs仍然是一个可行的选择。 AI

影响 KANs为高精度任务提供了卓越的泛化能力，而MLPs在资源受限的环境中仍然保持高效。

排序理由 比较两种模型架构的学术论文。

在 arXiv cs.AI 阅读 →

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KANs在结构化数据上优于MLPs，但计算成本更高

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报道来源 [3]

  1. arXiv cs.AI TIER_1 English(EN) · Matthew Steven P. Toledo, Justine Raphael H. Jacinto, Vivekjeet Singh Chambal, Rodolfo C. Camaclang III, Jamlech Iram N. Gojo Cruz, Reginald Neil C. Recario ·

    统计优势是否值得付出代价？KAN与MLP在结构化数据分类上的实证比较

    arXiv:2607.13413v1 Announce Type: cross Abstract: This study presents an empirical benchmarking comparison between Kolmogorov-Arnold Networks (KANs) and Multi-Layer Perceptrons (MLPs) on structured tabular classification tasks. Motivated by the growing interest in KANs as an alte…

  2. arXiv cs.AI TIER_1 English(EN) · Reginald Neil C. Recario ·

    统计优势是否值得付出代价？KAN与MLP在结构化数据分类上的实证比较

    This study presents an empirical benchmarking comparison between Kolmogorov-Arnold Networks (KANs) and Multi-Layer Perceptrons (MLPs) on structured tabular classification tasks. Motivated by the growing interest in KANs as an alternative function-approximating architecture, we ev…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    统计优势是否值得付出代价？KAN与MLP在结构化数据分类上的实证比较

    This study presents an empirical benchmarking comparison between Kolmogorov-Arnold Networks (KANs) and Multi-Layer Perceptrons (MLPs) on structured tabular classification tasks. Motivated by the growing interest in KANs as an alternative function-approximating architecture, we ev…

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