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English(EN) Mirror descent algorithms with logarithmic barriers

arXiv论文详细介绍了具有对数障碍的新型镜像下降算法

本文介绍了在使用对数障碍时,镜像下降和近镜像下降算法的新收敛保证。作者提出了一种方法,该方法避免了当解位于边界时Bregman散度爆炸的问题,并实现了具有恒定步长的最优速率。该研究还将此方法与现有的内点法进行了比较。 AI

影响 这项研究为可能支撑未来AI模型训练和开发的优化技术做出了贡献。

排序理由 详细介绍算法改进的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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arXiv论文详细介绍了具有对数障碍的新型镜像下降算法

本文如何被排名

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详细介绍算法改进的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Alberto De Marchi, Yura Malitsky, Adrien B. Taylor ·

    带对数障碍的镜像下降算法

    arXiv:2608.22834v2 Announce Type: replace-cross Abstract: We derive convergence guarantees for mirror descent and proximal mirror descent with a logarithmic barrier as the distance-generating function. When the solution lies on the boundary, the Bregman divergence blows up and cl…