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English(EN) Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms

Transformer预言机将边界基计算速度提升3.5倍

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种名为Oracle Border Basis Algorithm的新型深度学习方法，以加速符号代数中的计算。这种基于Transformer的预言机能够识别并移除传统边界基算法中计算成本高昂的约简步骤，在不牺牲准确性的前提下将速度提升高达3.5倍。该方法还引入了一种新的分词方案，显著减小了多项式的输入表示，使得该学习方法在数据效率方面更高，并且对于计算机代数系统更加实用。 AI

影响 这项研究可能显著加速符号计算任务，并可能影响依赖于多项式方程求解的领域。

排序理由 该集群包含一篇详细介绍新算法和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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Transformer预言机将边界基计算速度提升3.5倍

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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Hiroshi Kera, Nico Pelleriti, Yuki Ishihara, Max Zimmer, Sebastian Pokutta ·

    Attention in Computational Algebra: Transformer Oracles for Border Basis Algorithms

    arXiv:2505.23696v2 Announce Type: replace Abstract: Solving systems of polynomial equations, particularly those with finitely many solutions, is a crucial challenge across many scientific fields. Traditional methods like Gr\"obner and Border bases are fundamental but suffer from …

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