human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "performance analysis of evolutionary algorithms for the minimum label spanning tree problem"):
  Abstract: A few experimental investigations have shown that evolutionary algorithms (EAs) are efficient for the minimum label spanning tree (MLST) problem. However, we know little about that in theory. In this paper, we theoretically analyze the performances of the (1+1) EA, a simple version of EA, and a simple multiobjective evolutionary algorithm called GSEMO on the MLST problem. We reveal that for the    $\mathrm{MLST}_{b}$    problem, the (1+1) EA and GSEMO achieve a    $({b+1})/{2}$   -approximation ratio in expected polynomial runtime with respect to    $n$   , the number of nodes, and    $k$   , the number of labels. We also find that GSEMO achieves a    $(2\ln n+1)$   -approximation ratio for the MLST problem in expected polynomial runtime with respect to    $n$    and    $k$   . At the same time, we show that the (1+1) EA and GSEMO outperform local search algorithms on three instances of the MLST problem. We also construct an instance on which GSEMO outperforms the (1+1) EA.

Includes members:
  Member "a large population size can be unhelpful in evolutionary algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an adaptive and near parameter free evolutionary computation approach towards true automation in automl")
  Member "parameterized runtime analyses of evolutionary algorithms for the euclidean traveling salesperson problem":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parameterized complexity analysis of randomized search heuristics")
  Member "on the approximation ability of evolutionary optimization with application to minimum set cover":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "error analysis of elitist random search heuristics")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NE(Neural and Evolutionary Computing)