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: "the matching problem has no small symmetric sdp"
  Abstract: Yannakakis showed that the matching problem does not have a small symmetric linear program. Rothvo{\ss} recently proved that any, not necessarily symmetric, linear program also has exponential size. It is natural to ask whether the matching problem can be expressed compactly in a framework such as semidefinite programming (SDP) that is more powerful than linear programming but still allows efficient optimization. We answer this question negatively for symmetric SDPs: any symmetric SDP for the matching problem has exponential size. #R##N#We also show that an O(k)-round Lasserre SDP relaxation for the metric traveling salesperson problem yields at least as good an approximation as any symmetric SDP relaxation of size $n^k$. #R##N#The key technical ingredient underlying both these results is an upper bound on the degree needed to derive polynomial identities that hold over the space of matchings or traveling salesperson tours.

Connected through hyperedge HE-1 (induced by source paper "on the bit complexity of sum of squares proofs"):
  with members:
    - "sum of squares proofs and the quest toward optimal algorithms"
    - "hypercontractivity sum of squares proofs and their applications"

Connected through hyperedge HE-2 (induced by source paper "computing approximate psd factorizations"):
  with members:
    - "lower bounds on the size of semidefinite programming relaxations"
    - "on the existence of 0 1 polytopes with high semidefinite extension complexity"
    - "the matching polytope has exponential extension complexity"
    - "computing a nonnegative matrix factorization provably"
    - "on the complexity of nonnegative matrix factorization"

Connected through hyperedge HE-3 (induced by source paper "affine reductions for lps and sdps"):
  with members:
    - "average case polyhedral complexity of the maximum stable set problem"
    - "extension complexity of independent set polytopes"
    - "strong reductions for extended formulations"
    - "approximating rectangles by juntas and weakly exponential lower bounds for lp relaxations of csps"
    - "the matching polytope does not admit fully polynomial size relaxation schemes"
    - "no small linear program approximates vertex cover within a factor 2 epsilon"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "approximate constraint satisfaction requires large lp relaxations"

Connected through hyperedge HE-4 (induced by source paper "approximate constraint satisfaction requires large lp relaxations"):
  with members:
    - "lower bounds on the size of semidefinite programming relaxations"
    - "the matching polytope has exponential extension complexity"
    - "approximation limits of linear programs beyond hierarchies"
    - "an entropic proof of chang s inequality"
    - "extended formulations non negative factorizations and randomized communication protocols"
    - "max cut and the smallest eigenvalue"

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)