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 "PAC Learning Axis-aligned Rectangles with Respect to Product Distributions from Multiple-instance Examples"):
  Abstract: We describe a polynomial-time algorithm for learning axis-aligned rectangles in Q d with respect to product distributions from multiple-instance examples in the PAC model. Here, each example consists of n elements of Q d together with a label indicating whether any of the n points is in the rectangle to be learned. We assume that there is an unknown product distribution D over Q d such that all instances are independently drawn according to D. The accuracy of a hypothesis is measured by the probability that it would incorrectly predict whether one of n more points drawn from D was in the rectangle to be learned. Our algorithm achieves accuracy * with probability 1 ffi in

Includes members:
  Member "A General Lower Bound on the Number of Examples Needed for Learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Inductive Logic Programming")
  Member "Approximating Hyper-Rectangles: Learning and Pseudo-random Sets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "A General Lower Bound on the Number of Examples Needed for Learning")
  Member "Efficient Distribution-free Learning of Probabilistic Concepts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Learning in the Presence of Malicious Errors")
  Member "Solving the Multiple-Instance Problem with Axis-Parallel Rectangles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction")
  Member "A Note on Learning from Multiple-Instance Examples":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "A Framework for Multiple-Instance Learning")
  Member "A Framework for Multiple-Instance Learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Solving the Multiple-Instance Problem with Axis-Parallel Rectangles")

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