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: "AN ADAPTIVE NEURAL NETWORK PARSER"
  Abstract: We inv estigate the applicability of an adaptive neural network to problems with time-dependent input by demonstrating that a deterministic parser for natural language inputs of significant syntactic complexity can be developed using recurrent connectionist architectures. The traditional stacking mechanism, known to be necessary for proper treatment of context-free languages in symbolic systems, is absent from the design, having been subsumed by recurrency in the network.

Connected through hyperedge HE-1 (induced by source paper "Learning Context-free Grammars: Capabilities and Limitations of a Recurrent Neural Network with an External Stack Memory"):
  with members:
    - "A Connectionist Symbol Manipulator That Discovers the Structure of Context-Free Languages"
    - "Rule Revision with Recurrent Neural Networks"
    - "Using Prior Knowledge in an NNPDA to Learn Context-Free Languages"

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