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新论文探讨SVGD的Uniform-in-time Propagation-of-Chaos

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员发表了一篇论文，详细介绍了Stein Variational Gradient Descent (SVGD) 的Uniform-in-time Propagation-of-Chaos。该研究为广泛的分布度量引入了一种截止策略，产生了具有对数速率的propagation-of-chaos界限。对于特定的有限维情况，例如具有双线性核的高斯目标，SVGD动力学允许参数化速率，这些速率随时间保持一致。 AI

影响 这项研究有助于对机器学习中使用的优化算法的理论理解，可能影响未来的模型开发。

排序理由 该集群包含一篇在arXiv上发表的研究论文，详细介绍了机器学习算法的理论进展。

在 arXiv stat.ML 阅读 →

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新论文探讨SVGD的Uniform-in-time Propagation-of-Chaos

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该集群包含一篇在arXiv上发表的研究论文，详细介绍了机器学习算法的理论进展。
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报道来源 [2]

  1. arXiv stat.ML TIER_1 English(EN) · Krishnakumar Balasubramanian, Sayan Banerjee, Anna Korba ·

    Uniform-in-time Propagation-of-Chaos for Stein Variational Gradient Descent

    arXiv:2607.00149v1 Announce Type: cross Abstract: We study uniform-in-time propagation-of-chaos for continuous-time Stein Variational Gradient Descent (SVGD). Classical finite-time propagation-of-chaos estimates for mean-field systems typically deteriorate rapidly with time and t…

  2. arXiv stat.ML TIER_1 English(EN) · Anna Korba ·

    Uniform-in-time Propagation-of-Chaos for Stein Variational Gradient Descent

    We study uniform-in-time propagation-of-chaos for continuous-time Stein Variational Gradient Descent (SVGD). Classical finite-time propagation-of-chaos estimates for mean-field systems typically deteriorate rapidly with time and therefore do not directly explain the long-time rel…

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