human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Local Multivariate Binary Processors"
  Abstract: We thank Sue Becker, Peter Hancock and Darragh Smyth for helpful comments on this work. The work of Dario Floreano and Bill Phillips was supported by a Network Grant from the Human Capital and Mobility Programme of the European Community.

Connected through hyperedge HE-1 (induced by source paper "Unsupervised Neural Network Learning Procedures For Feature Extraction and Classification"):
  with members:
    - "LEARNING FACTORIAL CODES BY PREDICTABILITY MINIMIZATION (Neural Computation, 4(6):863-879, 1992)"
    - "VISIT: An Efficient Computational Model of Human Visual Attention"
    - "A Non-linear Information Maximisation Algorithm that Performs Blind Separation."
    - "Book Review New Kids on the Block way in the field of connectionist modeling. The"

Connected through hyperedge HE-2 (induced by source paper "Objective Function Formulation of the BCM Theory of Visual Cortical Plasticity: Statistical Connections, Stability Conditions"):
  with members:
    - "Theory of Synaptic Plasticity in Visual Cortex"
    - "Feature Extraction Using an Unsupervised Neural Network"
    - "Multimodality Exploration in Training an Unsupervised Projection Pursuit Neural Network"
    - "An integrated approach to the study of object features in visual recognition"
    - "Three-Dimensional Object Recognition Using an Unsupervised BCM Network: The Usefulness of Distinguishing Features"
    - "3D Object Recognition Using Unsupervised Feature Extraction"
    - "Classification of Underwater Mammals using Feature Extraction Based on Time-Frequency Analysis and BCM Theory"
    - "Combining Exploratory Projection Pursuit And Projection Pursuit Regression With Application To Neural Networks"

Question: Please tell me which class the center node 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