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: "approximate constraint satisfaction requires large lp relaxations"
  Abstract: We prove super-polynomial lower bounds on the size of linear programming relaxations for approximation versions of constraint satisfaction problems. We show that for these problems, polynomial-sized linear programs are exactly as powerful as programs arising from a constant number of rounds of the Sherali-Adams hierarchy. #R##N#In particular, any polynomial-sized linear program for Max Cut has an integrality gap of 1/2 and any such linear program for Max 3-Sat has an integrality gap of 7/8.

Connected through hyperedge HE-1 (induced by source paper "new dependencies of hierarchies in polynomial optimization"):
  with members:
    - "optimization over the boolean hypercube via sums of nonnegative circuit polynomials"
    - "on the bit complexity of sum of squares proofs"
    - "exact tensor completion with sum of squares"
    - "fast and robust tensor decomposition with applications to dictionary learning"
    - "the power of sherali adams relaxations for general valued csps"
    - "a 1 epsilon approximation for makespan scheduling with precedence constraints using lp hierarchies"
    - "noisy tensor completion via the sum of squares hierarchy"
    - "fast spectral algorithms from sum of squares proofs tensor decomposition and planted sparse vectors"

Connected through hyperedge HE-2 (induced by source paper "extended formulation lower bounds for refuting random csps"):
  with members:
    - "sum of squares lower bounds for refuting any csp"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "approximating rectangles by juntas and weakly exponential lower bounds for lp relaxations of csps"
    - "strongly refuting random csps below the spectral threshold"
    - "how to refute a random csp"
    - "complexity theoretic limitations on learning halfspaces"
    - "tensor prediction rademacher complexity and random 3 xor"
    - "lower bounds on the size of semidefinite programming relaxations"

Connected through hyperedge HE-3 (induced by source paper "on the power of symmetric linear programs"):
  with members:
    - "definable inapproximability new challenges for duplicator"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "on symmetric circuits and fixed point logics"
    - "the matching polytope has exponential extension complexity"

Connected through hyperedge HE-4 (induced by source paper "sherali adams strikes back"):
  with members:
    - "high dimensional estimation via sum of squares proofs"
    - "the power of sum of squares for detecting hidden structures"
    - "strongly refuting random csps below the spectral threshold"
    - "how to refute a random csp"
    - "subsampling mathematical relaxations and average case complexity"
    - "max cut and the smallest eigenvalue"

Connected through hyperedge HE-5 (induced by source paper "the power of sherali adams relaxations for general valued csps"):
  with members:
    - "binarisation for valued constraint satisfaction problems"
    - "algebraic properties of valued constraint satisfaction problem"
    - "a reduction from valued csp to min cost homomorphism problem for digraphs"
    - "the complexity of general valued csps"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "robustly solvable constraint satisfaction problems"
    - "sum of squares proofs and the quest toward optimal algorithms"
    - "half integrality lp branching and fpt algorithms"

Connected through hyperedge HE-6 (induced by source paper "query to communication lifting for bpp"):
  with members:
    - "entangled simultaneity versus classical interactivity in communication complexity"
    - "randomized query complexity of sabotaged and composed functions"
    - "nearly optimal separations between communication or query complexity and partitions"
    - "approximating rectangles by juntas and weakly exponential lower bounds for lp relaxations of csps"
    - "communication complexity of approximate nash equilibria"
    - "separations in query complexity based on pointer functions"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "an optimal lower bound on the communication complexity of gap hamming distance"

Connected through hyperedge HE-7 (induced by source paper "lower bounds for approximating the matching polytope"):
  with members:
    - "extension complexity of independent set polytopes"
    - "approximating rectangles by juntas and weakly exponential lower bounds for lp relaxations of csps"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "the matching polytope has exponential extension complexity"
    - "information equals amortized communication"

Connected through hyperedge HE-8 (induced by source paper "prediction with a short memory"):
  with members:
    - "beating the perils of non convexity guaranteed training of neural networks using tensor methods"
    - "sum of squares lower bounds for refuting any csp"
    - "lower bounds for csp refutation by sdp hierarchies"
    - "training input output recurrent neural networks through spectral methods"
    - "wavenet a generative model for raw audio"
    - "google s neural machine translation system bridging the gap between human and machine translation"
    - "how to refute a random csp"
    - "character aware neural language models"

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)