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: "approximation via correlation decay when strong spatial mixing fails"
  Abstract: Approximate counting via correlation decay is the core algorithmic technique used in the sharp delineation of the computational phase transition that arises in the approximation of the partition function of anti-ferromagnetic two-spin models. #R##N#Previous analyses of correlation-decay algorithms implicitly depended on the occurrence of strong spatial mixing (SSM). This means that one uses worst-case analysis of the recursive procedure that creates the sub-instances. We develop a new analysis method that is more refined than the worst-case analysis. We take the shape of instances in the computation tree into consideration and amortise against certain "bad" instances that are created as the recursion proceeds. This enables us to show correlation decay and to obtain an FPTAS even when SSM fails. #R##N#We apply our technique to the problem of approximately counting independent sets in hypergraphs with degree upper-bound Delta and with a lower bound k on the arity of hyperedges. Liu and Lin gave an FPTAS for k>=2 and Delta =3 and Delta =8. #R##N#Our technique also applies for larger values of k, giving an FPTAS for k>=Delta. This bound is not substantially stronger than existing randomised results in the literature. Nevertheless, it gives the first deterministic approximation scheme in this regime. Moreover, unlike existing results, it leads to an FPTAS for counting dominating sets in regular graphs with sufficiently large degree. #R##N#We further demonstrate that approximately counting independent sets in hypergraphs is NP-hard even within the uniqueness regime.

Connected through hyperedge HE-1 (induced by source paper "fast sampling and counting k sat solutions in the local lemma regime"):
  with members:
    - "algorithms for bis hard problems on expander graphs"
    - "algorithmic pirogov sinai theory"
    - "counting hypergraph colorings in the local lemma regime"
    - "convergence of mcmc and loopy bp in the tree uniqueness region for the hard core model"
    - "a faster approximation algorithm for the gibbs partition function"
    - "approximate counting the lovasz local lemma and inference in graphical models"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "new constructive aspects of the lovasz local lemma"

Connected through hyperedge HE-2 (induced by source paper "counting solutions to random cnf formulas"):
  with members:
    - "counting independent sets and colorings on random regular bipartite graphs"
    - "counting hypergraph colorings in the local lemma regime"
    - "sampling random colorings of sparse random graphs"
    - "approximate counting the lovasz local lemma and inference in graphical models"
    - "on the concentration of the number of solutions of random satisfiability formulas"
    - "new constructive aspects of the lovasz local lemma"
    - "deterministic algorithms for the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-3 (induced by source paper "counting hypergraph colorings in the local lemma regime"):
  with members:
    - "improved bounds for randomly sampling colorings via linear programming"
    - "a polynomial time approximation algorithm for all terminal network reliability"
    - "uniform sampling through the lov asz local lemma"
    - "approximate counting the lovasz local lemma and inference in graphical models"
    - "commutativity in the algorithmic lovasz local lemma"
    - "an algorithmic proof of the lovasz local lemma via resampling oracles"
    - "new constructive aspects of the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-4 (induced by source paper "approximate counting the lovasz local lemma and inference in graphical models"):
  with members:
    - "uniform sampling through the lov asz local lemma"
    - "inapproximability of the partition function for the antiferromagnetic ising and hard core models"
    - "computing the independence polynomial in shearer s region for the lll"
    - "computing the independence polynomial from the tree threshold down to the roots"
    - "commutativity in the algorithmic lovasz local lemma"
    - "an algorithmic proof of the lovasz local lemma via resampling oracles"
    - "fptas for counting monotone cnf"
    - "approximation algorithms for two state anti ferromagnetic spin systems on bounded degree graphs"

Connected through hyperedge HE-5 (induced by source paper "uniform sampling through the lov asz local lemma"):
  with members:
    - "what can be sampled locally"
    - "inapproximability of the partition function for the antiferromagnetic ising and hard core models"
    - "approximate counting the lovasz local lemma and inference in graphical models"
    - "an algorithmic proof of the lovasz local lemma via resampling oracles"
    - "fptas for counting monotone cnf"
    - "new constructive aspects of the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-6 (induced by source paper "counting hypergraph matchings up to uniqueness threshold"):
  with members:
    - "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"
    - "counting independent sets in hypergraphs when strong spatial mixing fails"
    - "fptas for hardcore and ising models on hypergraphs"
    - "the complexity of approximately counting in 2 spin systems on k uniform bounded degree hypergraphs"
    - "fptas for weighted fibonacci gates and its applications"
    - "a simple fptas for counting edge covers"
    - "spatial mixing and the connective constant optimal bounds"

Connected through hyperedge HE-7 (induced by source paper "the complexity of approximately counting in 2 spin systems on k uniform bounded degree hypergraphs"):
  with members:
    - "inapproximability of the partition function for the antiferromagnetic ising and hard core models"
    - "counting hypergraph matchings up to uniqueness threshold"
    - "fptas for counting monotone cnf"
    - "inapproximability after uniqueness phase transition in two spin systems"
    - "approximation algorithms for two state anti ferromagnetic spin systems on bounded degree graphs"
    - "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)