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English(EN) Linear convergence of proximal descent schemes on the Wasserstein space

新数学论文详述Wasserstein空间上的优化

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了在Wasserstein空间上优化泛函的新方法，Wasserstein空间是理解概率分布至关重要的数学概念。该工作为近邻下降方案建立了线性收敛性，放宽了对测地凸性的先前要求。这项进展利用了均匀对数Sobolev不等式和熵“三明治”引理，扩展了先前研究并解决了与方案中相对Fisher信息定义相关的挑战。 AI

排序理由 该聚类包含一篇发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新数学论文详述Wasserstein空间上的优化

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该聚类包含一篇发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Razvan-Andrei Lascu, Mateusz B. Majka, David \v{S}i\v{s}ka, {\L}ukasz Szpruch ·

    Wasserstein空间上近端下降方案的线性收敛性

    arXiv:2411.15067v2 Announce Type: replace-cross Abstract: We investigate proximal descent methods, inspired by the minimizing movement scheme introduced by Jordan, Kinderlehrer and Otto, for optimizing entropy-regularized functionals on the Wasserstein space. We establish linear …

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