Budget-Dependent Convergence Rate of Stochastic Approximation

  title={Budget-Dependent Convergence Rate of Stochastic Approximation},
  author={Pierre L'Ecuyer and Gang George Yin},
  journal={SIAM Journal on Optimization},
Convergence rate results are derived for a stochastic optimization problem where a performance measure is minimized with respect to a vector parameter θ. Assuming that a gradient estimator is available and that both the bias and the variance of the estimator are (known) functions of the budget devoted to its computation, the gradient estimator is employed in conjunction with a stochastic approximation (SA) algorithm. Our interest is to figure out how to allocate the total available… CONTINUE READING
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