human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "The EM Algorithm for Mixtures of Factor Analyzers"):
  Abstract: Technical Report CRG-TR-96-1 May 21, 1996 (revised Feb 27, 1997) Abstract Factor analysis, a statistical method for modeling the covariance structure of high dimensional data using a small number of latent variables, can be extended by allowing different local factor models in different regions of the input space. This results in a model which concurrently performs clustering and dimensionality reduction, and can be thought of as a reduced dimension mixture of Gaussians. We present an exact Expectation-Maximization algorithm for fitting the parameters of this mixture of factor analyzers.

Includes members:
  Member "Data Mining for Association Rules with Unsupervised Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Recognizing Handwritten Digits Using Mixtures of Linear Models")
  Member "Data Mining for Association Rules with Unsupervised Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Recognizing Handwritten Digits Using Mixtures of Linear Models")
  Member "A HIERARCHICAL COMMUNITY OF EXPERTS":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Generative Models for Discovering Sparse Distributed Representations")
  Member "EM Algorithms for PCA and SPCA":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Supervised learning from incomplete data via an EM approach")
  Member "Recognizing Handwritten Digits Using Mixtures of Linear Models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Constraint Tangent Distance for On-line Character Recognition")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Neural_Networks