human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "more effective crossover operators for the all pairs shortest path problem"
  Abstract: The all-pairs shortest path problem is the first non-artificial problem for which it was shown that adding crossover can significantly speed up a mutation-only evolutionary algorithm. Recently, the analysis of this algorithm was refined and it was shown to have an expected optimization time (w.r.t. the number of fitness evaluations) of $\Theta(n^{3.25}(\log n)^{0.25})$. #R##N#In contrast to this simple algorithm, evolutionary algorithms used in practice usually employ refined recombination strategies in order to avoid the creation of infeasible offspring. We study extensions of the basic algorithm by two such concepts which are central in recombination, namely \emph{repair mechanisms} and \emph{parent selection}. We show that repairing infeasible offspring leads to an improved expected optimization time of $\mathord{O}(n^{3.2}(\log n)^{0.2})$. As a second part of our study we prove that choosing parents that guarantee feasible offspring results in an even better optimization time of $\mathord{O}(n^{3}\log n)$. #R##N#Both results show that already simple adjustments of the recombination operator can asymptotically improve the runtime of evolutionary algorithms.

Connected through hyperedge HE-1 (induced by source paper "black box complexity of the binary value function"):
  with members:
    - "optimal parameter choices via precise black box analysis"
    - "runtime analysis of the 1 λ λ genetic algorithm on random satisfiable 3 cnf formulas"
    - "ranking based black box complexity"
    - "reducing the arity in unbiased black box complexity"
    - "playing mastermind with constant size memory"
    - "faster black box algorithms through higher arity operators"

Connected through hyperedge HE-2 (induced by source paper "fast genetic algorithms"):
  with members:
    - "the 1 λ evolutionary algorithm with self adjusting mutation rate"

Connected through hyperedge HE-3 (induced by source paper "the sampling and learning framework a statistical view of evolutionary algorithms"):
  with members:
    - "performance analysis of evolutionary algorithms for the minimum label spanning tree problem"
    - "multiplicative drift analysis"
    - "parameterized runtime analyses of evolutionary algorithms for the euclidean traveling salesperson problem"
    - "on the approximation ability of evolutionary optimization with application to minimum set cover"
    - "on the complexity of trial and error"
    - "a new method for lower bounds on the running time of evolutionary algorithms"
    - "multi view active learning in the non realizable case"

Connected through hyperedge HE-4 (induced by source paper "reducing the arity in unbiased black box complexity"):
  with members:
    - "black box complexity breaking the o n log n barrier of leadingones"
    - "multiplicative drift analysis"
    - "black box complexities of combinatorial problems"
    - "playing mastermind with constant size memory"
    - "faster black box algorithms through higher arity operators"

Connected through hyperedge HE-5 (induced by source paper "black box complexities of combinatorial problems"):
  with members:
    - "simple max min ant systems and the optimization of linear pseudo boolean functions"
    - "faster black box algorithms through higher arity operators"

Question: Please tell me which class the center node 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)