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: "Exploiting Choice: Instruction Fetch and Issue on an Implementable Simultaneous Multithreading Processor"
  Abstract: Simultaneous multithreading is a technique that permits multiple independent threads to issue multiple instructions each cycle. In previous work we demonstrated the performance potential of simultaneous multithreading, based on a somewhat idealized model. In this paper we show that the throughput gains from simultaneous multithreading can be achieved without extensive changes to a conventional wide-issue superscalar, either in hardware structures or sizes. We present an architecture for simultaneous multithreading that achieves three goals: (1) it minimizes the architectural impact on the conventional superscalar design, (2) it has minimal performance impact on a single thread executing alone, and (3) it achieves significant throughput gains when running multiple threads. Our simultaneous multithreading architecture achieves a throughput of 5.4 instructions per cycle, a 2.5-fold improvement over an unmodified superscalar with similar hardware resources. This speedup is enhanced by an advantage of multithreading previously unexploited in other architectures: the ability to favor for fetch and issue those threads most efficiently using the processor each cycle, thereby providing the best instructions to the processor.

Connected through hyperedge HE-1 (induced by source paper "Multipath Execution: Opportunities and Limits"):
  with members:
    - "Threaded Multiple Path Execution"
    - "Limited Dual Path Execution"
    - "Selective Eager Execution on the PolyPath Architecture"

Connected through hyperedge HE-2 (induced by source paper "Converting Thread-Level Parallelism to Instruction-Level Parallelism via Simultaneous Multithreading"):
  with members:
    - "d d Techniques for Extracting Instruction Level Parallelism on MIMD Architectures"
    - "d d MISC: A Multiple Instruction Stream Computer"

Connected through hyperedge HE-3 (induced by source paper "Dynamic Hammock Predication for Non-predicated Instruction Set Architectures"):
  with members:
    - "Limited Dual Path Execution"
    - "Selective Eager Execution on the PolyPath Architecture"
    - "Confidence Estimation for Speculation Control"
    - "A Comparison of Full and Partial Predicated Execution Support for ILP Processors"

Connected through hyperedge HE-4 (induced by source paper "Threaded Multiple Path Execution"):
  with members:
    - "Multipath Execution: Opportunities and Limits"
    - "Limited Dual Path Execution"
    - "Selective Eager Execution on the PolyPath Architecture"

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: Rule_Learning