Kullback-Leibler距离与统计模型

Tomohiro Washino, Tadashi Takahashi
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引用次数: 0

摘要

当前位置Kullback-Leibler距离是在19世纪的统计力学中发现的,它是一个被称为相对熵的概念。在20世纪,人们开始认识到它是统计学和学习理论中的重要数量。我们不仅可以在欧几里得空间中定义它,而且可以在一般概率分布中展开这个概念。Kullback-Leibler距离不仅是一个重要的概念,而且推导了一个算法。Kullback-Leibler距离不仅是一个重要的概念,而且可以推导出算法。对于Kullback-Leibler距离的信息科学意义及其与数学性质的关系,存在着许多未知的结构。利用计算机代数系统构造了一些关于极点的例子,并探讨了极点的性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kullback-Leibler Distance and Statatistical Model
: Kullback-Leibler distance is discovered in statistical mechanics of the 19th century and is a concept called the relative entropy. In the 20th century, it came to be known that it is important quantity in statistics and learning theory. We cannot only define it in Euclidean space, but also can expand the concept in general probability distribution. Kullback-Leibler distance is not only important as the concept, but also derive an algorithm. Kullback-Leibler distance is not only an important concept, but also it can derive the algorithm. As for the information science meaning of Kullback-Leibler distance and the relations with the mathematic properties, there exist many unknown structures. We constituted some examples about the pole using a computer algebra system and explored the properties.
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