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: "Logarithmic Time Parallel Bayesian Inference"
  Abstract: I present a parallel algorithm for exact probabilistic inference in Bayesian networks. For polytree networks with n variables, the worst-case time complexity is O(log n) on a CREW PRAM (concurrent-read, exclusive-write parallel random-access machine) with n processors, for any constant number of evidence variables. For arbitrary networks, the time complexity is O(r 3w log n) for n processors, or O(w log n) for r 3w n processors, where r is the maximum range of any variable, and w is the induced width (the maximum clique size), after moralizing and trian gulating the network.

Connected through hyperedge HE-1 (induced by source paper "Logarithmic-Time Updates and Queries in Probabilistic Networks"):
  with members:
    - "Towards a Better Understanding of Memory-Based Reasoning Systems"

Connected through hyperedge HE-2 (induced by source paper "Global Conditioning for Probabilistic Inference in Belief Networks"):
  with members:
    - "BUCKET ELIMINATION: A UNIFYING FRAMEWORK FOR PROBABILISTIC INFERENCE"
    - "Structured Representation of Complex Stochastic Systems"
    - "Topological Parameters for time-space tradeoff"
    - "Automated Decomposition of Model-based Learning Problems"

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: Probabilistic_Methods