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: "a complexity dichotomy for hypergraph partition functions"
  Abstract: We consider the complexity of counting homomorphisms from an $r$-uniform hypergraph $G$ to a symmetric $r$-ary relation $H$. We give a dichotomy theorem for $r>2$, showing for which $H$ this problem is in FP and for which $H$ it is #P-complete. This generalises a theorem of Dyer and Greenhill (2000) for the case $r=2$, which corresponds to counting graph homomorphisms. Our dichotomy theorem extends to the case in which the relation $H$ is weighted, and the goal is to compute the \emph{partition function}, which is the sum of weights of the homomorphisms. This problem is motivated by statistical physics, where it arises as computing the partition function for particle models in which certain combinations of $r$ sites interact symmetrically. In the weighted case, our dichotomy theorem generalises a result of Bulatov and Grohe (2005) for graphs, where $r=2$. When $r=2$, the polynomial time cases of the dichotomy correspond simply to rank-1 weights. Surprisingly, for all $r>2$ the polynomial time cases of the dichotomy have rather more structure. It turns out that the weights must be superimposed on a combinatorial structure defined by solutions of an equation over an Abelian group. Our result also gives a dichotomy for a closely related constraint satisfaction problem.

Connected through hyperedge HE-1 (induced by source paper "fptas for counting monotone cnf"):
  with members:
    - "inapproximability of the partition function for the antiferromagnetic ising and hard core models"
    - "fptas for weighted fibonacci gates and its applications"
    - "a simple fptas for counting edge covers"
    - "a polynomial time algorithm for estimating the partition function of the ferromagnetic ising model on a regular matroid"
    - "approximate counting via correlation decay on planar graphs"
    - "approximation algorithms for two state anti ferromagnetic spin systems on bounded degree graphs"
    - "correlation decay up to uniqueness in spin systems"
    - "approximate counting via correlation decay in spin systems"

Connected through hyperedge HE-2 (induced by source paper "the complexity of weighted and unweighted csp"):
  with members:
    - "non negative weighted csps an effective complexity dichotomy"
    - "a decidable dichotomy theorem on directed graph homomorphisms with non negative weights"
    - "graph homomorphisms with complex values a dichotomy theorem"
    - "the complexity of weighted boolean csp"
    - "the complexity of weighted boolean csp with mixed signs"
    - "a complexity dichotomy for partition functions with mixed signs"
    - "an approximation trichotomy for boolean csp"

Connected through hyperedge HE-3 (induced by source paper "counting homomorphisms and partition functions"):
  with members:
    - "the complexity of weighted boolean csp"
    - "a complexity dichotomy for partition functions with mixed signs"

Connected through hyperedge HE-4 (induced by source paper "an effective dichotomy for the counting constraint satisfaction problem"):
  with members:
    - "the complexity of weighted and unweighted csp"
    - "the complexity of weighted boolean csp"

Connected through hyperedge HE-5 (induced by source paper "a complexity dichotomy for partition functions with mixed signs"):
  with members:
    - "inapproximability of the tutte polynomial"

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)