RKHS will be an essential tool for establishing a connection between Regularization Theory and Statistical Learning Theory.

RKHS是结合正规化理论和统计学理论的必要工具。

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We discuss at length the properties of a very important class of kernels which lead to the key notion of Reproducing kernel Hilbert Space (RKHS).

我们将详细的讨论核心课程中十分重要的特质，其引导出再生核希尔伯特空间理论(RKHS)中一个非常关键的概念。

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We first provide the background to the concept of Hilbert space, introduce RKHS, and then clarify the relation between smoothness and apriori knowledge on the solution in RKHS.

因此我们首先需了解希伯特空间背景的基本观念，接着针对RKHS的解释说明平滑算法和先验算法之间的关系。

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We first provide the background to the concept of Hilbert space, introduce RKHS, and then clarify the relation between smoothness and apriori knowledge on the solution in RKHS.

因此我们首先需了解希伯特空间背景的基本观念，接着针对RKHS的解释说明平滑算法和先验算法之间的关系。

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