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Atypicality for the class of exponential family

机译:指数族的非典型性

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Atypicality is a new concept that uses a codelength-based deviation from the norm to find the interesting rare events. In a previous paper we have developed an information theoretic approach for discrete data. Then in the two other papers, we came up with an extension to the real-valued models for Gaussian and vector Gaussian cases. In the current paper we generalize our real-valued model to the class of exponential family. We include a comprehensive table that summarize the approximated atypicality criterion and bounds for common distributions in the exponential family model.
机译:非典型性是一个新概念,它使用基于码长的偏离规范来发现有趣的稀有事件。在先前的论文中,我们已经为离散数据开发了一种信息理论方法。然后在其他两篇论文中,我们对高斯和向量高斯案例的实值模型进行了扩展。在本文中,我们将实值模型推广到指数族。我们包括一个综合表,该表总结了近似的非典型性准则和指数族模型中常见分布的范围。

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