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: "settling the complexity of local max cut almost completely"
  Abstract: We consider the problem of finding a local optimum for Max-Cut with FLIP-neighborhood, in which exactly one node changes the partition. Schaeffer and Yannakakis (SICOMP, 1991) showed PLS-completeness of this problem on graphs with unbounded degree. On the other side, Poljak (SICOMP, 1995) showed that in cubic graphs every FLIP local search takes O(n^2) steps, where n is the number of nodes. Due to the huge gap between degree three and unbounded degree, Ackermann, Roeglin, and Voecking (JACM, 2008) asked for the smallest d for which the local Max-Cut problem with FLIP-neighborhood on graphs with maximum degree d is PLS-complete. In this paper, we prove that the computation of a local optimum on graphs with maximum degree five is PLS-complete. Thus, we solve the problem posed by Ackermann et al. almost completely by showing that d is either four or five (unless PLS is in P). On the other side, we also prove that on graphs with degree O(log n) every FLIP local search has probably polynomial smoothed complexity. Roughly speaking, for any instance, in which the edge weights are perturbated by a (Gaussian) random noise with variance \sigma^2, every FLIP local search terminates in time polynomial in n and \sigma^{-1}, with probability 1-n^{-\Omega(1)}. Putting both results together, we may conclude that although local Max-Cut is likely to be hard on graphs with bounded degree, it can be solved in polynomial time for slightly perturbated instances with high probability.

Connected through hyperedge HE-1 (induced by source paper "graphical one sided markets"):
  with members:
    - "schelling games on graphs"
    - "swap stability in schelling games on graphs"
    - "maximin share allocations on cycles"
    - "schelling segregation with strategic agents"
    - "fair allocation of indivisible items with externalities"
    - "almost envy free allocations with connected bundles"
    - "fair division of a graph"
    - "fair division via social comparison"

Connected through hyperedge HE-2 (induced by source paper "smoothed complexity of local max cut and binary max csp"):
  with members:
    - "smoothed efficient algorithms and reductions for network coordination games"
    - "local max cut in smoothed polynomial time"
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"

Connected through hyperedge HE-3 (induced by source paper "computational complexity of hedonic games on sparse graphs"):
  with members:
    - "hedonic coalition formation for distributed task allocation among wireless agents"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "stable partitions in additively separable hedonic games"

Connected through hyperedge HE-4 (induced by source paper "beyond worst case analysis"):
  with members:
    - "being robust in high dimensions can be practical"
    - "implicit regularization in deep learning"
    - "a friendly smoothed analysis of the simplex method"
    - "how to escape saddle points efficiently"
    - "local max cut in smoothed polynomial time"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "understanding deep learning requires rethinking generalization"
    - "how robust are reconstruction thresholds for community detection"

Connected through hyperedge HE-5 (induced by source paper "local max cut in smoothed polynomial time"):
  with members:
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"

Connected through hyperedge HE-6 (induced by source paper "computing stable outcomes in symmetric additively separable hedonic games"):
  with members:
    - "simple causes of complexity in hedonic games"
    - "stable partitions in additively separable hedonic games"
    - "computing the nucleolus of weighted voting games"

Connected through hyperedge HE-7 (induced by source paper "dynamics of profit sharing games"):
  with members:
    - "improving the price of anarchy for selfish routing via coordination mechanisms"
    - "efficient coordination mechanisms for unrelated machine scheduling"
    - "combinatorial auctions with decreasing marginal utilities"

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.CC(Computational Complexity)