human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "average case polyhedral complexity of the maximum stable set problem"):
  Abstract: We study the minimum number of constraints needed to formulate random instances of the maximum stable set problem via linear programs (LPs), in two distinct models. In the uniform model, the constraints of the LP are not allowed to depend on the input graph, which should be encoded solely in the objective function. There we prove a $$2^{\Omega (n{/}\log n)}$$2Ω(n/logn) lower bound with probability at least $$1 - 2^{-2^n}$$1-2-2n for every LP that is exact for a randomly selected set of instances; each graph on at most n vertices being selected independently with probability $$p \geqslant 2^{- \left( {\begin{array}{c}n/4\\ 2\end{array}}\right) + n}$$pź2-n/42+n. In the non-uniform model, the constraints of the LP may depend on the input graph, but we allow weights on the vertices. The input graph is sampled according to the G(n, p) model. There we obtain upper and lower bounds holding with high probability for various ranges of p. We obtain a super-polynomial lower bound all the way from $$p = \Omega \left( \frac{\log ^{6+\varepsilon } n}{n} \right) $$p=Ωlog6+źnn to $$p = o\left( \frac{1}{\log n} \right) $$p=o1logn. Our upper bound is close to this as there is only an essentially quadratic gap in the exponent, which currently also exists in the worst-case model. Finally, we state a conjecture that would close this gap, both in the average-case and worst-case models.

Includes members:
  Member "the matching polytope does not admit fully polynomial size relaxation schemes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lifting linear extension complexity bounds to the mixed integer setting")
  Member "lower bounds on the size of semidefinite programming relaxations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lifting with simple gadgets and applications to circuit and proof complexity")
  Member "approximate constraint satisfaction requires large lp relaxations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "new dependencies of hierarchies in polynomial optimization")
  Member "the matching polytope has exponential extension complexity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "extended formulation lower bounds for refuting random csps")
  Member "approximation limits of linear programs beyond hierarchies":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "compressing permutation groups into grammars and polytopes a graph embedding approach")

Question: Please tell me which class the source paper 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)