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 "lower bounds for approximating the matching polytope"):
  Abstract: We prove that any extended formulation that approximates the matching polytope on $n$-vertex graphs up to a factor of $(1+\varepsilon)$ for any $\frac2n \le \varepsilon \le 1$ must have at least $\binom{n}{{\alpha}/{\varepsilon}}$ defining inequalities where $0<\alpha<1$ is an absolute constant. This is tight as exhibited by the $(1+\varepsilon)$ approximating linear program obtained by dropping the odd set constraints of size larger than $({1+\varepsilon})/{\varepsilon}$ from the description of the matching polytope. Previously, a tight lower bound of $2^{\Omega(n)}$ was only known for $\varepsilon = O\left(\frac{1}{n}\right)$ [Rothvoss, STOC '14; Braun and Pokutta, IEEE Trans. Information Theory '15] whereas for $\frac2n \le \varepsilon \le 1$, the best lower bound was $2^{\Omega\left({1}/{\varepsilon}\right)}$ [Rothvoss, STOC '14]. The key new ingredient in our proof is a close connection to the non-negative rank of a lopsided version of the unique disjointness matrix.

Includes members:
  Member "extension complexity of independent set polytopes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lifting with simple gadgets and applications to circuit and proof complexity")
  Member "approximating rectangles by juntas and weakly exponential lower bounds for lp relaxations of csps":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "list decodable subspace recovery")
  Member "lower bounds on the size of semidefinite programming relaxations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (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-5 (induced by source paper "extended formulation lower bounds for refuting random csps")
  Member "information equals amortized communication":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "communication for generating correlation a unifying survey")

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)