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 "better fixed arity unbiased black box algorithms"):
  Abstract: In their GECCO'12 paper, Doerr and Doerr proved that the k-ary unbiased black-box complexity of O ne M ax  on n bits is O(n/k) for 2 ≤ k ≤ log2 n. We propose an alternative strategy for achieving this unbiased black-box complexity when 3 ≤ k ≤ log2 n. While it is based on the same idea of block-wise optimization, it uses k-ary unbiased operators in a different way.   For each block of size 2k-1 - 1 we set up, in O(k) queries, a virtual coordinate system, which enables us to use an arbitrary unrestricted algorithm to optimize this block. This is possible because this coordinate system introduces a bijection between unrestricted queries and a subset of k-ary unbiased operators. We note that this technique does not depend on O ne M ax  being solved and can be used in more general contexts.   This together constitutes an algorithm which is conceptually simpler than the one by Doerr and Doerr, and in the same time achieves better constant multiples in the asymptotic notation. Our algorithm works in (2 + o(1)) · n/(k - 1), where o(1) relates to k. Our experimental evaluation of this algorithm shows its efficiency already for 3 ≤ k ≤ 6.

Includes members:
  Member "optimal parameter choices via precise black box analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "probabilistic tools for the analysis of randomized optimization heuristics")
  Member "optimal parameter choices through self adjustment applying the 1 5 th rule in discrete settings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "runtime performances of randomized search heuristics for the dynamic weighted vertex cover problem")
  Member "ranking based black box complexity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "probabilistic tools for the analysis of randomized optimization heuristics")
  Member "reducing the arity in unbiased black box complexity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "black box complexity of the binary value function")
  Member "playing mastermind with constant size memory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "black box complexity of the binary value function")
  Member "faster black box algorithms through higher arity operators":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "benchmarking discrete optimization heuristics with iohprofiler")

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)