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: "Is Learning The n-th Thing Any Easier Than Learning The First?"
  Abstract: This paper investigates learning in a lifelong context. Lifelong learning addresses situations in which a learner faces a whole stream of learning tasks. Such scenarios provide the opportunity to transfer knowledge across multiple learning tasks, in order to generalize more accurately from less training data. In this paper, several different approaches to lifelong learning are described, and applied in an object recognition domain. It is shown that across the board, lifelong learning approaches generalize consistently more accurately from less training data, by their ability to transfer knowledge across learning tasks.

Connected through hyperedge HE-1 (induced by source paper "Clustering Learning Tasks and the Selective Cross-Task Transfer of Knowledge"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Transferring and Retraining Learned Information Filters"):
  with members:
    - "Incremental Reduced Error Pruning"
    - "Learning Trees and Rules with Set-valued Features"
    - "Context-sensitive learning methods for text categorization"
    - "Feature Generation for Sequence Categorization"

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