符合形状的镜子下降与对数偏差
Amanjit Singh Kainth1,2, Ting-Kam Leonard Wong3, Frank Rudzicz1,2
1Department of Computer Science, University of Toronto, Toronto, Canada.
概括
我们介绍了 conformal mirror descent,一种新的算法,可以扩展布雷格曼分歧,以获得最佳的运输和凸的二元性. 这种方法为通用指数家族的连续时间优化和在线估计提供了新的见解.
科学领域:
- 优化理论 优化理论
- 机器学习 机器学习
- 信息几何学信息几何学
背景情况:
- 逻辑分歧扩展了布雷格曼分歧,从最佳运输和通用凸两性中得出结论.
- 这种分歧具有显著的数学特性,并产生独特的几何结构.
研究的目的:
- 为了引入符合性镜像下降,这是连续时间镜像下降的概括.
- 分析这个新算法的动态和收性质.
- 将该方法应用于在线估计和梯度流构造.
主要方法:
- 使用由对数分歧诱导的几何.
- 在一般化镜像图下推导符合性镜像下降的动态.
- 证明连续时间收结果.
- 将算法应用于概括的指数家族估计.
主要成果:
- 符合镜像的下降被证明是赫森梯度流的时间变化.
- 在连续时间中建立了收.
- 该方法已成功应用于在线估计和通过迪里克莱特最佳运输在单元简单上构建梯度流.
结论:
- 符合镜像下降为连续时间优化问题提供了一个强大的新工具.
- 该框架为在线学习和统计模型中的几何分析提供了新的方法.
- 与最佳运输和梯度流的连接为进一步研究开辟了道路.
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