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arXiv 2102.08685math.PRmath.OCstat.ML
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平均随机逼近的偏差不等式

Deviation inequalities for stochastic approximation by averaging

Xiequan Fan, Pierre Alquier, Paul Doukhan

摘要:

引入了一类马尔可夫链,它包含了平均和非平均的随机逼近模型。利用鞅逼近的方法,建立了这类链上的Lipschitz函数的各种偏差不等式,并将这些不等式应用于平均和经验风险最小化的随机随机变量中.

英文摘要:

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 and empirical risk minimisation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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