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: "In Proceedings of the 1997 Sian Kaan International Workshop on Neural Networks and Neurocontrol. Real-Valued"
  Abstract: 2 Neural Network & Machine Learning Laboratory Computer Science Department Brigham Young University Provo, UT 84602, USA Email: martinez@cs.byu.edu WWW: http://axon.cs.byu.edu Abstract. Many neural network models must be trained by finding a set of real-valued weights that yield high accuracy on a training set. Other learning models require weights on input attributes that yield high leave-one-out classification accuracy in order to avoid problems associated with irrelevant attributes and high dimensionality. In addition, there are a variety of general problems for which a set of real values must be found which maximize some evaluation function. This paper presents an algorithm for doing a schemata search over a real-valued weight space to find a set of weights (or other real values) that yield high values for a given evaluation function. The algorithm, called the Real-Valued Schemata Search (RVSS), uses the BRACE statistical technique [Moore & Lee, 1993] to determine when to narrow the search space. This paper details the RVSS approach and gives initial empirical results.

Connected through hyperedge HE-1 (induced by source paper "Instance Pruning Techniques"):
  with members:
    - "Bias and the Probability of Generalization"

Connected through hyperedge HE-2 (induced by source paper "An Overview of Evolutionary Computation"):
  with members:
    - "A COMPRESSION ALGORITHM FOR PROBABILITY TRANSITION MATRICES"
    - "An Evolutionary Approach to Combinatorial Optimization Problems"
    - "EVOLVING REPRESENTATIONS OF DESIGN CASES AND THEIR USE IN CREATIVE DESIGN"

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