Abstract
The quasigradient algorithm of stochastic optimization is considered. The conditions to be imposed on the step multiplier, for Cesaro convergence of the algorithms with probability 1, are studied. Adaptive step adjustment is proposed, and the convergence of the corresponding algorithm is proved. A numerical algorithm containing heuristic elements is described. The results of numerical experiments are quoted.
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