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 "Confidence Estimation for Speculation Control"):
  Abstract: Modern processors improve instruction level parallelism by speculation. The outcome of data and control decisions is predicted, and the operations are speculatively executed and only committed if the original predictions were correct. There are a number of other ways that processor resources could be used, such as threading or eager execution. As the use of speculation increases, we believe more processors will need some form of speculation control to balance the benefits of speculation against other possible activities. Confidence estimation is one technique that can be exploited by architects for speculation control. In this paper, we introduce performance metrics to compare confidence estimation mechanisms, and argue that these metrics are appropriate for speculation control. We compare a number of confidence estimation mechanisms, focusing on mechanisms that have a small implementation cost and gain benefit by exploiting characteristics of branch predictors, such as clustering of mispredicted branches. We compare the performance of the different confidence estimation methods using detailed pipeline simulations. Using these simulations, we show how to improve some confidence estimators, providing better insight for future investigations comparing and applying confidence estimators.

Includes members:
  Member "Dynamic Hammock Predication for Non-predicated Instruction Set Architectures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "A Comparison of Full and Partial Predicated Execution Support for ILP Processors")
  Member "Limited Dual Path Execution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Multipath Execution: Opportunities and Limits")
  Member "Selective Eager Execution on the PolyPath Architecture":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Multipath Execution: Opportunities and Limits")

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