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: "A Performance Analysis of CNS-1 on Sparse Connectionist Networks"
  Abstract: This report deals with the efficient mapping of sparse neural networks on CNS-1. We develop parallel vector code for an idealized sparse network and determine its performance under three memory systems. We use the code to evaluate the memory systems (one of which will be implemented in the prototype), and to pinpoint bottlenecks in the current CNS-1 design.

Connected through hyperedge HE-1 (induced by source paper "All-to-all Broadcast on the CNS-1"):
  with members:
    - "A Performance Analysis of the CNS-1 on Large, Dense Backpropagation Networks Connectionist Network Supercomputer"

Connected through hyperedge HE-2 (induced by source paper "A Supercomputer for Neural Computation"):
  with members:
    (none)

Connected through hyperedge HE-3 (induced by source paper "A Performance Analysis of the CNS-1 on Large, Dense Backpropagation Networks Connectionist Network Supercomputer"):
  with members:
    - "All-to-all Broadcast on the CNS-1"

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