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English(EN) Stationary Bias and Extrapolation in Nonlinear Two-Timescale Stochastic Approximation

arXiv论文分析非线性两时间尺度随机逼近中的平稳偏差

作者 PulseAugur 编辑部 · [2 个来源] ·

本文深入探讨了非线性两时间尺度随机逼近方法中存在的平稳偏差。研究聚焦于由有限状态马尔可夫链驱动的递归，推导了一个一阶偏差展开，即使当慢步长远小于快步长时，该展开也保持一致性。研究结果表明，偏差缩减策略需要仔细匹配Richardson-Romberg外插权重与特定的步长路径，因为偏差指数可能并非总是整数。研究包含一个可精确求解的非线性马尔可夫示例用于验证，并考察了时序差分学习和有限运行外插。 AI

排序理由 该聚类包含一篇发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv论文分析非线性两时间尺度随机逼近中的平稳偏差

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该聚类包含一篇发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · A. Ch. Madhusudanarao, Rahul Singh ·

    非线性两时间尺度随机逼近中的固定偏差和外插

    arXiv:2610.10246v1 Announce Type: new Abstract: Constant-step stochastic approximation generally has a nonzero stationary mean error that persists under time averaging. This paper studies that error for nonlinear two-timescale recursions driven by an exogenous finite-state Markov…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    非线性两时间尺度随机逼近中的固定偏差和外插

    Constant-step stochastic approximation generally has a nonzero stationary mean error that persists under time averaging. This paper studies that error for nonlinear two-timescale recursions driven by an exogenous finite-state Markov chain. Under stated smoothness assumptions and …

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