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: "APPROXIMATION IN L p (R d FROM SPACES SPANNED BY THE PERTURBED INTEGER TRANSLATES OF"
  Abstract: May 14, 1995 Abstract. The problem of approximating smooth L p -functions from spaces spanned by the integer translates of a radially symmetric function is very well understood. In case the points of translation, ffi, are scattered throughout R d , the approximation problem is only well understood in the "stationary" setting. In this work, we treat the "non-stationary" setting under the assumption that ffi is a small perturbation of Z d . Our results, which are similar in many respects to the known results for the case ffi = Z d , apply specifically to the examples of the Gauss kernel and the Generalized Multiquadric.

Connected through hyperedge HE-1 (induced by source paper "Radial basis function approximation: from gridded centers to scattered centers"):
  with members:
    - "Radial Basis Functions: L p -approximation orders with scattered centres"
    - "Negative observations concerning approximations from spaces generated by scattered shifts of functions vanishing at 1"
    - "Approximation from shift-invariant subspaces of L"

Connected through hyperedge HE-2 (induced by source paper "Radial Basis Functions: L p -approximation orders with scattered centres"):
  with members:
    - "AN UPPER BOUND ON THE APPROXIMATION POWER OF PRINCIPAL SHIFT-INVARIANT SPACES"
    - "Radial basis function approximation: from gridded centers to scattered centers"

Connected through hyperedge HE-3 (induced by source paper "AN UPPER BOUND ON THE APPROXIMATION POWER OF PRINCIPAL SHIFT-INVARIANT SPACES"):
  with members:
    - "Radial Basis Functions: L p -approximation orders with scattered centres"

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