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 "Topological Parameters for time-space tradeoff"):
  Abstract: In this paper we propose a family of algorithms combining tree-clustering with conditioning that trade space for time. Such algorithms are useful for reasoning in probabilistic and deterministic networks as well as for accomplishing optimization tasks. By analyzing the problem structure it will be possible to select from a spectrum the algorithm that best meets a given time-space specifica tion.

Includes members:
  Member "BUCKET ELIMINATION: A UNIFYING FRAMEWORK FOR PROBABILISTIC INFERENCE":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Robustness Analysis of Bayesian Networks with Finitely Generated Convex Sets of Distributions")
  Member "Global Conditioning for Probabilistic Inference in Belief Networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Automated Decomposition of Model-based Learning Problems")

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: Probabilistic_Methods