We define $K_{\mathbf{a}, \mathbf{b}}$ as the $n \times m$ matrix whose $ij^{th}$ entry is $\kappa(a_{i}, b_{j})$
Where, $\kappa$ is a (positive definite) kernel function.
Here, $\mathbf{a}_{i}, \mathbf{b}_{j} \in \mathbb{R}^{D} \hspace{10pt} \forall \hspace{3pt}0 \leq i < n, 0 \leq j < m$
Here $D \neq n, m$ in general
Show that $K_{\mathbf{a},\mathbf{a}} - K_{\mathbf{a},\mathbf{b}}K_{\mathbf{b},\mathbf{b}}^{-1}K_{\mathbf{b},\mathbf{a}}$ is positive definite
I came across this matrix as the covariance matrix of distribution when studying sparse Gaussian processes. Tried but couldn't prove it is pd.