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: "approximately counting h colourings is bis hard"
  Abstract: We consider the problem of counting H-colourings from an input graph G to a target graph H. We show that if H is any fixed graph without trivial components, then the problem is as hard as the well-known problem #BIS, which is the problem of (approximately) counting independent sets in a bipartite graph. #BIS is a complete problem in an important complexity class for approximate counting, and is believed not to have an FPRAS. If this is so, then our result shows that for every graph H without trivial components, the H-colouring counting problem has no FPRAS. This problem was studied a decade ago by Goldberg, Kelk and Paterson. They were able to show that approximately sampling H-colourings is #BIS-hard, but it was not known how to get the result for approximate counting. Our solution builds on non-constructive ideas using the work of Lovasz.

Connected through hyperedge HE-1 (induced by source paper "lower bounds for testing graphical models colorings and antiferromagnetic ising models"):
  with members:
    - "approximating pairwise correlations in the ising model"
    - "learning graphical models using multiplicative weights"
    - "sample optimal identity testing with high probability"
    - "structure learning of h colorings"
    - "a new approach for testing properties of discrete distributions"
    - "testing ising models"
    - "bis hardness for 2 spin systems on bipartite bounded degree graphs in the tree non uniqueness region"
    - "inapproximability of the partition function for the antiferromagnetic ising and hard core models"

Connected through hyperedge HE-2 (induced by source paper "approximate counting csp seen from the other side"):
  with members:
    - "constraint solving via fractional edge covers"
    - "a dichotomy theorem for nonuniform csps"
    - "the proof of csp dichotomy conjecture"
    - "the complexity of approximating conservative counting csps"
    - "the challenges of unbounded treewidth in parameterised subgraph counting problems"
    - "understanding model counting for beta acyclic cnf formulas"
    - "complexity of counting csp with complex weights"
    - "an effective dichotomy for the counting constraint satisfaction problem"

Connected through hyperedge HE-3 (induced by source paper "the complexity of approximately counting retractions"):
  with members:
    - "surjective h colouring new hardness results"
    - "a dichotomy theorem for nonuniform csps"
    - "the complexity of approximately counting tree homomorphisms"
    - "ferromagnetic potts model refined bis hardness and related results"
    - "the complexity of surjective homomorphism problems a survey"
    - "an approximation trichotomy for boolean csp"

Connected through hyperedge HE-4 (induced by source paper "structure learning of h colorings"):
  with members:
    - "a dichotomy theorem for nonuniform csps"
    - "the proof of csp dichotomy conjecture"
    - "hardness of parameter estimation in graphical models"
    - "maximum likelihood bounded tree width markov networks"
    - "correlation decay up to uniqueness in spin systems"
    - "computational transition at the uniqueness threshold"

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)