This paper presents a numerical comparison between algorithms for unconstrained optimization that take account of sparsity in the second derivative matrix of the objective function. Some of the ...

This is a preview. Log in through your library . Abstract The sparsity constrained rank-one matrix approximation problem is a difficult mathematical optimization problem which arises in a wide array ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...