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Update convexity.md #1388

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Expand Up @@ -86,7 +86,7 @@ $$\lambda a + (1-\lambda) b \in \mathcal{X} \text{ 当 } a, b \in \mathcal{X}.
:label:`fig_nonconvex`

通常，深度学习中的问题是在凸集上定义的。
例如，$\mathbb{R}^d$，即实数的$d$-维向量的集合是凸集（毕竟$\mathbb{R}^d$中任意两点之间的线存在$\mathbb{R}^d$）中。
例如，$\mathbb{R}^d$，即实数的$d$-维向量的集合是凸集（毕竟$\mathbb{R}^d$中任意两点之间的线存在于$\mathbb{R}^d$）中。
在某些情况下，我们使用有界长度的变量，例如球的半径定义为$\{\mathbf{x} | \mathbf{x} \in \mathbb{R}^d \text{ 且 } \| \mathbf{x} \| \leq r\}$。

### 凸函数
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