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 "Limited Dual Path Execution"):
  Abstract: This work presents a hybrid branch predictor scheme that uses a limited form of dual path execution along with dynamic branch prediction to improve execution times. The ability to execute down both paths of a conditional branch enables the branch penalty to be minimized; however, relying exclusively on dual path execution is infeasible due because instruction fetch rates far exceed the capability of the pipeline to retire a single branch before others must be processed. By using confidence information, available in the dynamic branch prediction state tables, a limited form of dual path execution becomes feasible. This reduces the burden on the branch predictor by allowing predictions of low confidence to be avoided. In this study we present a new approach to gather branch prediction confidence with little or no overhead, and use this confidence mechanism to determine whether dual path execution or branch prediction should be used. Comparing this hybrid predictor model to the dynamic branch predictor shows a dramatic decrease in misprediction rate, which translates to an reduction in runtime of over 20%. These results imply that dual path execution, which often is thought to be an excessively resource consuming method, may be a worthy approach if restricted with an appropriate predicting set.

Includes members:
  Member "Multipath Execution: Opportunities and Limits":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Selective Eager Execution on the PolyPath Architecture")
  Member "Dynamic Hammock Predication for Non-predicated Instruction Set Architectures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Confidence Estimation for Speculation Control")
  Member "Threaded Multiple Path Execution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Multipath Execution: Opportunities and Limits")
  Member "d d The Effects of Predicated Execution on Branch Prediction":
    also connected through other hyperedges:
      (none)
  Member "Selective Eager Execution on the PolyPath Architecture":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Multipath Execution: Opportunities and Limits")
  Member "Confidence Estimation for Speculation Control":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Dynamic Hammock Predication for Non-predicated Instruction Set Architectures")

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: Rule_Learning