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: "Capacity of SDM"
  Abstract: Report R95:12 ISRN : SICS-R--95/12-SE ISSN : 0283-3638 Abstract A more efficient way of reading the SDM memory is presented. This is accomplished by using implicit information, hitherto not utilized, to find the information-carrying units and thus removing unnecessary noise when reading the memory.

Connected through hyperedge HE-1 (induced by source paper "Some Comments on the Information Stored in Sparse Distributed Memory"):
  with members:
    - "Best Probability of Activation and Performance Comparisons for Several Designs of Sparse Distributed Memory"
    - "Convergence and new operations in SDM new method for converging in the SDM memory, utilizing"

Connected through hyperedge HE-2 (induced by source paper "Convergence and new operations in SDM new method for converging in the SDM memory, utilizing"):
  with members:
    - "Best Probability of Activation and Performance Comparisons for Several Designs of Sparse Distributed Memory"
    - "Some Comments on the Information Stored in Sparse Distributed Memory"

Connected through hyperedge HE-3 (induced by source paper "Best Probability of Activation and Performance Comparisons for Several Designs of Sparse Distributed Memory"):
  with members:
    - "Some Comments on the Information Stored in Sparse Distributed Memory"
    - "Convergence and new operations in SDM new method for converging in the SDM memory, utilizing"

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