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 "Combining Exploratory Projection Pursuit And Projection Pursuit Regression With Application To Neural Networks"):
  Abstract: We present a novel classification and regression method that combines exploratory projection pursuit (unsupervised training) with projection pursuit regression (supervised training), to yield a new family of cost/complexity penalty terms. Some improved generalization properties are demonstrated on real world problems.

Includes members:
  Member "Objective Function Formulation of the BCM Theory of Visual Cortical Plasticity: Statistical Connections, Stability Conditions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Receptive Fields for Vision: from Hyperacuity to Object Recognition")
  Member "Feature Extraction Using an Unsupervised Neural Network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain")
  Member "On the Combination of Supervised and Unsupervised Learning  reducing the overall error measure of a classifier.":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Feature Extraction Using an Unsupervised Neural Network")
  Member "PHONETIC CLASSIFICATION OF TIMIT SEGMENTS PREPROCESSED WITH LYON'S COCHLEAR MODEL USING A SUPERVISED/UNSUPERVISED HYBRID NEURAL NETWORK":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Feature Extraction Using an Unsupervised Neural Network")
  Member "Face Recognition using a Hybrid Supervised/Unsupervised Neural Network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Multimodality Exploration in Training an Unsupervised Projection Pursuit Neural Network")
  Member "Extraction of Facial Features for Recognition using Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Ensemble Training: Some Recent Experiments with Postal Zip Data")

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