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 "settling the complexity of computing approximate two player nash equilibria"):
  Abstract: We prove that there exists a constant $\epsilon>0$ such that, assuming the Exponential Time Hypothesis for PPAD, computing an $\epsilon$-approximate Nash equilibrium in a two-player (nXn) game requires quasi-polynomial time, $n^{\log^{1-o(1)} n}$. This matches (up to the o(1) term) the algorithm of Lipton, Markakis, and Mehta [LMM03]. #R##N#Our proof relies on a variety of techniques from the study of probabilistically checkable proofs (PCP); this is the first time that such ideas are used for a reduction between problems inside PPAD. #R##N#En route, we also prove new hardness results for computing Nash equilibria in games with many players. In particular, we show that computing an $\epsilon$-approximate Nash equilibrium in a game with n players requires $2^{\Omega(n)}$ oracle queries to the payoff tensors. This resolves an open problem posed by Hart and Nisan [HN13], Babichenko [Bab14], and Chen et al. [CCT15]. In fact, our results for n-player games are stronger: they hold with respect to the $(\epsilon,\delta)$-WeakNash relaxation recently introduced by Babichenko et al. [BPR16].

Includes members:
  Member "almost polynomial ratio eth hardness of approximating densest k subgraph":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimizing item and subgroup configurations for social aware vr shopping")
  Member "detecting communities is hard and counting them is even harder":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "eth hardness of approximating 2 csps and directed steiner network")
  Member "approximating nash equilibria in tree polymatrix games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tree polymatrix games are ppad hard")
  Member "the query complexity of correlated equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "near optimal communication lower bounds for approximate nash equilibria")
  Member "communication complexity of approximate nash equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "complexity theory game theory and economics the barbados lectures")
  Member "inapproximability results for approximate nash equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "public bayesian persuasion being almost optimal and almost persuasive")
  Member "well supported versus approximate nash equilibria query complexity of large games":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "near optimal communication lower bounds for approximate nash equilibria")
  Member "near optimal hardness results for signaling in bayesian games":
    also connected through other hyperedges:
      (none)

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)