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: "Unsupervised Neural Network Learning Procedures For Feature Extraction and Classification"
  Abstract: Technical report CNS-TR-95-1 Center for Neural Systems McMaster University

Connected through hyperedge HE-1 (induced by source paper "Local Multivariate Binary Processors"):
  with members:
    - "Objective Function Formulation of the BCM Theory of Visual Cortical Plasticity: Statistical Connections, Stability Conditions"

Connected through hyperedge HE-2 (induced by source paper "Book Review New Kids on the Block way in the field of connectionist modeling. The"):
  with members:
    - "Efficient Visual Search: A Connectionist Solution"

Connected through hyperedge HE-3 (induced by source paper "A Non-linear Information Maximisation Algorithm that Performs Blind Separation."):
  with members:
    - "An information-maximisation approach to blind separation and blind deconvolution"
    - "Plasticity-Mediated Competitive Learning"

Connected through hyperedge HE-4 (induced by source paper "LEARNING FACTORIAL CODES BY PREDICTABILITY MINIMIZATION (Neural Computation, 4(6):863-879, 1992)"):
  with members:
    - "An information-maximisation approach to blind separation and blind deconvolution"
    - "LEARNING COMPLEX, EXTENDED SEQUENCES USING THE PRINCIPLE OF HISTORY COMPRESSION (Neural Computation, 4(2):234-242, 1992)"
    - "Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain"
    - "Plasticity-Mediated Competitive Learning"
    - "SEMILINEAR PREDICTABILITY MINIMIZATION PRODUCES WELL-KNOWN FEATURE DETECTORS Neural Computation, 1996 (accepted)"

Connected through hyperedge HE-5 (induced by source paper "VISIT: An Efficient Computational Model of Human Visual Attention"):
  with members:
    - "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex."
    - "Efficient Visual Search: A Connectionist Solution"
    - "A Delay-Line Based Motion Detection Chip"

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