Abstract: Factorizing a low-rank matrix into two matrix factors with low dimensions from its noisy observations is a classical but challenging problem arising from real-world applications. This paper ...

Within this repo there are 2 simple programs that calculate covariances for a set of inputs on the GPU. Each program calculates these matrices either in the simple, traditional manner, or in an ...

In the theory of vector spaces, a set of vectors is said to be linearly independent if there exists no nontrivial linear combination of the vectors that equals the zero vector. If such a linear ...

This is a preview. Log in through your library . Abstract In this paper we consider estimating the rank of an unknown symmetric matrix based on a symmetric, asymptotically normal estimator of the ...

A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization ...

Matrix-covariate is now frequently encountered in many biomedical researches. It is common to fit conventional statistical models by vectorizing matrix-covariate. This strategy results in a large ...