human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "On the Effect of Analog Noise in Discrete-Time Analog Computations"):
  Abstract: We introduce a model for analog computation with discrete time in the presence of analog noise that is flexible enough to cover the most important concrete cases, such as noisy analog neural nets and networks of spiking neurons. This model subsumes the classical model for digital computation in the presence of noise. We show that the presence of arbitrarily small amounts of analog noise reduces the power of analog computational models to that of finite automata, and we also prove a new type of upper bound for the

Includes members:
  Member "Vapnik-Chervonenkis Dimension of Recurrent Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "POWER OF NEURAL NETS")
  Member "Constructing Deterministic Finite-State Automata in Recurrent Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Analog Neural Nets with Gaussian or other Common Noise Distributions cannot Recognize Arbitrary Regular Languages")
  Member "Analog Neural Nets with Gaussian or other Common Noise Distributions cannot Recognize Arbitrary Regular Languages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Constructing Deterministic Finite-State Automata in Recurrent Neural Networks")
  Member "TURING COMPUTABILITY WITH NEURAL NETS":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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: Theory