We present a simple proof for bounding the smallest eigenvalue of the empirical covariance in a causal Gaussian process. Along the way, we establish a one-sided tail inequality for Gaussian quadratic forms using a causal decomposition. Our proof only uses elementary facts about the Gaussian distribution and the union bound.
翻译:我们提出一个简单的证据,证明在因果性高斯进程中将实验性共变最小的半数值捆绑在一起。 沿着这条路,我们用因果分解为高斯二次方形建立了片面的尾部不平等。 我们的证据只使用关于高斯分布和结合约束的基本事实。