Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

This is a preview. Log in through your library . Abstract A rate of convergence of the conjugate gradient method for minimizing the convex quadratic functionals in Hilbert space is investigated.

The EM algorithm is a very popular and widely applicable algorithm for the computation of maximum likelihood estimates. Although its implementation is generally simple, the EM algorithm often exhibits ...