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 resistant predicates from pairwise independence"
  Abstract: We study the approximability of predicates on $k$ variables from a domain $[q]$, and give a new sufficient condition for such predicates to be approximation resistant under the Unique Games Conjecture. Specifically, we show that a predicate $P$ is approximation resistant if there exists a balanced pairwise independent distribution over $[q]^k$ whose support is contained in the set of satisfying assignments to $P$.

Connected through hyperedge HE-1 (induced by source paper "on the approximability of presidential type predicates"):
  with members:
    - "on the approximation resistance of balanced linear threshold functions"
    - "a characterization of approximation resistance"

Connected through hyperedge HE-2 (induced by source paper "on the approximation resistance of balanced linear threshold functions"):
  with members:
    - "a dichotomy theorem for nonuniform csps"
    - "sum of squares lower bounds for refuting any csp"
    - "a characterization of approximation resistance for even k partite csps"
    - "a characterization of approximation resistance"
    - "on the usefulness of predicates"

Connected through hyperedge HE-3 (induced by source paper "sum of squares lower bounds for refuting any csp"):
  with members:
    - "lower bounds for csp refutation by sdp hierarchies"
    - "the backtracking survey propagation algorithm for solving random k sat problems"
    - "strongly refuting random csps below the spectral threshold"
    - "how to refute a random csp"
    - "noisy tensor completion via the sum of squares hierarchy"
    - "complexity theoretic limitations on learning halfspaces"
    - "sum of squares lower bounds from pairwise independence"
    - "lower bounds on the size of semidefinite programming relaxations"

Connected through hyperedge HE-4 (induced by source paper "how to refute a random csp"):
  with members:
    - "complexity theoretic limitations on learning halfspaces"
    - "sum of squares lower bounds from pairwise independence"
    - "tensor prediction rademacher complexity and random 3 xor"
    - "analysis of boolean functions"
    - "subsampled power iteration a unified algorithm for block models and planted csp s"
    - "sum of squares proofs and the quest toward optimal algorithms"
    - "from average case complexity to improper learning complexity"
    - "more data speeds up training time in learning halfspaces over sparse vectors"

Connected through hyperedge HE-5 (induced by source paper "satisfiability of ordering csps above average"):
  with members:
    - "analysis of boolean functions"
    - "local search is better than random assignment for bounded occurrence ordering k csps"
    - "simultaneously satisfying linear equations over mathbb f _2 maxlin2 and max r lin2 parameterized above average"
    - "constraint satisfaction problems parameterized above or below tight bounds a survey"
    - "parameterized complexity of maxsat above average"
    - "all ternary permutation constraint satisfaction problems parameterized above average have kernels with quadratic numbers of variables"
    - "betweenness parameterized above tight lower bound"
    - "a probabilistic approach to problems parameterized above or below tight bounds"

Connected through hyperedge HE-6 (induced by source paper "parameterized algorithms for constraint satisfaction problems above average with global cardinality constraints"):
  with members:
    - "analysis of boolean functions"
    - "hypercontractivity sum of squares proofs and their applications"
    - "better balance by being biased a 0 8776 approximation for max bisection"
    - "approximating csps with global cardinality constraints using sdp hierarchies"
    - "note on maximal bisection above tight lower bound"
    - "reductions between expansion problems"
    - "a probabilistic approach to problems parameterized above or below tight bounds"
    - "solving max r sat above a tight lower bound"

Connected through hyperedge HE-7 (induced by source paper "approximate hypergraph coloring under low discrepancy and related promises"):
  with members:
    - "super polylogarithmic hypergraph coloring hardness via low degree long codes"
    - "constructive discrepancy minimization for convex sets"
    - "on the usefulness of predicates"
    - "constructive discrepancy minimization by walking on the edges"
    - "constructive algorithms for discrepancy minimization"
    - "approximate graph coloring by semidefinite programming"

Connected through hyperedge HE-8 (induced by source paper "refuting unique game conjecture"):
  with members:
    - "strengthened hardness for approximating minimum unique game and small set expansion"
    - "on the usefulness of predicates"
    - "agnostic learning of monomials by halfspaces is hard"

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)