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: "All-to-all Broadcast on the CNS-1"
  Abstract: This study deals with the all-to-all broadcast on the CNS-1. We determine a lower bound for the run time and present an algorithm meeting this bound. Since this study points out a bottleneck in the network interface, we also analyze the performance of alternative interface designs. Our analyses are based on a run time model of the network.

Connected through hyperedge HE-1 (induced by source paper "A Performance Analysis of CNS-1 on Sparse Connectionist Networks"):
  with members:
    - "A Supercomputer for Neural Computation"
    - "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 Performance Analysis of the CNS-1 on Large, Dense Backpropagation Networks Connectionist Network Supercomputer"):
  with members:
    - "A Performance Analysis of CNS-1 on Sparse Connectionist Networks"

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