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English(EN) It's all In the (Exponential) Family: An Equivalence between Maximum Likelihood Estimation and Control Variates for Sketching Algorithms

新研究将最大似然估计与机器学习算法中的控制变量联系起来

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员在机器学习的草图算法中，建立了最大似然估计（MLE）与控制变量估计器（CVE）之间的理论等价性。这种在指数族特定条件下证明的等价性表明，最优的CVE可以达到与MLE相同的渐近方差，从而为MLE提供一种不动点算法。实验结果表明，与传统的MLE求根方法相比，这种不动点方法在速度和数值稳定性方面都有所提高，尤其是在双变量正态分布的情况下。 AI

影响 这项研究可能为训练依赖于最大似然估计的机器学习模型带来更有效和可复现的方法。

排序理由 该集群包含一篇详细介绍机器学习统计学理论发现的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

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新研究将最大似然估计与机器学习算法中的控制变量联系起来

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该集群包含一篇详细介绍机器学习统计学理论发现的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Keegan Kang, Kerong Wang, Ding Zhang, Rameshwar Pratap, Bhisham Dev Verma, Benedict H. W. Wong ·

    都在（指数级）家族中：最大似然估计与控制变量在草图算法中的等价性

    arXiv:2601.22378v3 Announce Type: replace Abstract: Maximum likelihood estimators (MLE) and control variate estimators (CVE) have been used in conjunction with known information across sketching algorithms and applications in machine learning. We prove that under certain conditio…

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