Gaussian variational approximation is a popular methodology to approximate posterior distributions in Bayesian inference, especially high-dimensional and large data settings. To control the computational cost, while being able capture correlations among variables, low rank plus diagonal structure was introduced previous literature for covariance matrix. For specific learning task, uniqueness of...