All Questions

I'm working with a high-dimensional covariance matrix and exploring Kronecker product approximations to make it computationally manageable. Here's the setup: I have a graph $G$ represented by a $D\...

I am interested in approximating a symmetric matrix in a block diagonal form, i.e. compute just some entries of the matrix located in blocks around the diagonal. Are there any theoretical guarantees ...

The usual conjugate gradient type algorithms for iteratively finding the inverse of a matrix applied to a vector, $x = A^{-1} y$, works by minimizing $\|Ax - y\|^2$ where $\| \cdot \|$ is the $L^2$-...

Consider the generalized eigenvalue problem : $ \Sigma_{XY} \Sigma_{YX} {W} = \lambda \Sigma_{XX} {W} $ where $\Sigma_{XX} $ and $\Sigma_{XY}$ are sample covariance matrices are of the matrices $X$...

Hi, my question is similar to this one. I have to compute $B^TC^{−1}B$, where $C$ is a strictly positive definite $n\times n$ matrix and $B$ is $n\times m$. The matrix $C$ is huge ($n$ up to a ...