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: "SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training"
  Abstract: We report on our development of a high-performance system for neural network and other signal processing applications. We have designed and implemented a vector microprocessor and packaged it as an attached processor for a conventional workstation. We present performance comparisons with commercial workstations on neural network backpropagation training. The SPERT-II system demonstrates significant speedups over extensively hand optimization code running on the workstations.

Connected through hyperedge HE-1 (induced by source paper "A Fast Kohonen Net Implementation for"):
  with members:
    - "References "Using Neural Networks to Identify Jets", Kohonen, "Self Organized Formation of Topologically Correct Feature"

Connected through hyperedge HE-2 (induced by source paper "Quicknet on MultiSpert: Fast Parallel Neural Network Training"):
  with members:
    - "MBP on T0: mixing floating- and fixed-point formats in BP learning"

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