Estimates of the rate of convergence for certain minimization algorithms for strongly convex functions

The convergence of certain minimization algorithms for strongly convex functions is investigated. Namely, convergence with the rate of a geometric progression is proved for the method of coordinatewise descent and one variant of the method of feasible directions. An estimate of the ratio of the progression in dependence on the number of variables is given for the method of coordinatewise descent.
Bibliography: 3 titles.