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English(EN) Approximation Error Upper and Lower Bounds for Hölder Class with Transformers

研究人员确立 Transformer 近似误差界限

研究人员为 Transformer 模型应用于 Hölder 类函数时的近似误差确立了精确的上下界。该研究推导出了一个新的上界,表明具有特定数量块的 Transformer 可以以期望的精度近似任何有界 Hölder 函数。此外,该论文首次提供了严格证明,说明 Transformer 需要最少数量的块才能达到一定的近似精度,证明了它们在回归任务中的经验有效性。 AI

影响 提供了对 Transformer 在函数逼近能力和局限性的理论理解。

排序理由 学术论文发布在 arXiv 上,详细介绍了 Transformer 模型的理论界限。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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研究人员确立 Transformer 近似误差界限

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学术论文发布在 arXiv 上,详细介绍了 Transformer 模型的理论界限。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jerry Zhijian Yang ·

    Transformers对Hölder类近似误差的上下界

    We explore the expressive power of Transformers by establishing precise approximation error upper and lower bounds for Hölder class. Specifically, a new approximation upper bound is derived for the standard Transformer architecture equipped with Softmax operators, ReLU activation…