Table 1:

Dimensions (number of features) | p |

Data | , point n, feature i |

Masks | |

Cluster label | k |

Total number of clusters | K |

Mixture weight, cluster mean, covariance | |

Probability density function of the multivariate gaussian distribution | |

Total number of data points | N |

Number of points for which feature i is masked | |

Noise mean for feature i | |

Noise variance for feature i | |

Virtual features (random variable) | |

Mean of virtual feature | |

Variance of virtual feature | |

Log likelihood of in
cluster k | |

Set of data points assigned to cluster k | |

Subset of for which feature i is
fully masked |

Dimensions (number of features) | p |

Data | , point n, feature i |

Masks | |

Cluster label | k |

Total number of clusters | K |

Mixture weight, cluster mean, covariance | |

Probability density function of the multivariate gaussian distribution | |

Total number of data points | N |

Number of points for which feature i is masked | |

Noise mean for feature i | |

Noise variance for feature i | |

Virtual features (random variable) | |

Mean of virtual feature | |

Variance of virtual feature | |

Log likelihood of in
cluster k | |

Set of data points assigned to cluster k | |

Subset of for which feature i is
fully masked |

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