Let $X$ be an $n\times n$ symmetric random matrix with independent but non-identically distributed entries. The deviation inequalities of the spectral norm of $X$ with Gaussian entries have been obtained by using the standard concentration of Gaussian measure results. This paper establishes an upper tail bound of the spectral norm of $X$ with sub-exponential entries. Our method relies upon a crucial ingredient of a novel chaining argument that essentially involves both the particular structure of the sets used for the chaining and the distribution of coordinates of a point on the unit sphere.

中文翻译：

---

次指数随机矩阵谱范数的尾界

让$X$豆$n\times n$具有独立但不相同分布的条目的对称随机矩阵。谱范数的偏差不等式$X$通过使用高斯测量结果的标准浓度获得了高斯条目。本文建立了谱范数的尾上界$X$与次指数条目。我们的方法依赖于一种新颖的链接论证的关键要素，该论证本质上涉及用于链接的集合的特定结构以及单位球体上点的坐标分布。