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English(EN) Gauss-Newton Accuracy and Indefinite Hessians: Uniform Coexistence in Low-Cost Sets

新论文探讨高斯-牛顿精度与不定Hessian

本文深入探讨了脊正则化非线性最小二乘法中高斯-牛顿曲率的精度。在局部正则性和持续的水平集曲率的特定条件下,本文证明了两种不同的曲率机制可以统一共存。研究证明了全局最小值的存在,并提供了它们相对Hessian误差的界限,同时还识别出同一低成本集合中表现出具有更高相对误差的不定Hessian的点。研究进一步详细说明了正脊盖如何在各种扰动下发挥作用,并证明了随着脊权重接近零,这些邻域保持稳定。引入了逐点证书来管理Hessian校正分量,并推导出了针对不同预测图和脊的精确相对误差界限。此外,本文还提供了说明输出对齐、曲率方向和持久性影响的解析示例,以及一个结构性结果,该结果证实了低成本集合中的全雅可比矩阵行秩以及在秩亏损参考附近的精确插值。 AI

排序理由 该项目是一篇研究论文,详细介绍了数学和算法发现。[lever_c_研究降级:ic=1 ai=0.1]

在 Hugging Face Daily Papers 阅读 →

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新论文探讨高斯-牛顿精度与不定Hessian

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该项目是一篇研究论文,详细介绍了数学和算法发现。[lever_c_研究降级:ic=1 ai=0.1]
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  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Gauss-Newton 精度与不定 Hessian:低成本集合中的统一共存

    We study the accuracy of Gauss-Newton curvature in ridge-regularized nonlinear least squares. Under local regularity and persistence of level-set curvature magnitude along an exact-fit section, we prove uniform coexistence of two curvature regimes. Global minimizers exist, and ev…