We introduce a class of Markov chains, that contains the model of stochastic approximation by averaging and non-averaging. Using martingale approximation method, we establish various deviation inequalities for separately Lipschitz functions of such a chain, with different moment conditions on some dominating random variables of martingale differences.Finally, we apply these inequalities to the stochastic approximation by averaging.
翻译:我们引入了一组 Markov 链, 它包含平均和非平均的随机近似模型。 我们使用马丁加勒近近似法,为这种链条的单独利普施奇茨功能设定了不同的偏差不平等, 并给某些随机随机的马丁加尔差异设定了不同的时间条件。 最后, 我们将这些不平等以平均方式应用到随机近近似中 。