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: "detecting communities is hard and counting them is even harder"
  Abstract: We consider the algorithmic problem of community detection in networks. Given an undirected friendship graph $G=\left(V,E\right)$, a subset $S\subseteq V$ is an $\left(\alpha,\beta\right)$-community if: #R##N#* Every member of the community is friends with an $\alpha$-fraction of the community; #R##N#* Every non-member is friends with at most a $\beta$-fraction of the community. #R##N#Arora et al [AGSS12] gave a quasi-polynomial time algorithm for enumerating all the $\left(\alpha,\beta\right)$-communities for any constants $\alpha>\beta$. #R##N#Here, we prove that, assuming the Exponential Time Hypothesis (ETH), quasi-polynomial time is in fact necessary - and even for a much weaker approximation desideratum. Namely, distinguishing between: #R##N#* $G$ contains an $\left(1,o\left(1\right)\right)$-community; and #R##N#* $G$ does not contain an $\left(\beta+o\left(1\right),\beta\right)$-community for any $\beta\in\left[0,1\right]$. #R##N#We also prove that counting the number of $\left(1,o\left(1\right)\right)$-communities requires quasi-polynomial time assuming the weaker #ETH.

Connected through hyperedge HE-1 (induced by source paper "eth hardness of approximating 2 csps and directed steiner network"):
  with members:
    - "hardness of approximate nearest neighbor search"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "improved approximation algorithms for projection games"
    - "distributed pcp theorems for hardness of approximation in p"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "approximating spanners and directed steiner forest upper and lower bounds"
    - "approximation of non boolean 2csp"
    - "polynomially low error pcps with polyloglog n queries via modular composition"

Connected through hyperedge HE-2 (induced by source paper "inapproximability of vc dimension and littlestone s dimension"):
  with members:
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "on the approximability of partial vc dimension"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "a birthday repetition theorem and complexity of approximating dense csps"
    - "eth hardness for densest k subgraph with perfect completeness"
    - "complexity theoretic limitations on learning halfspaces"
    - "eth hardness for signaling in symmetric zero sum games"
    - "hardness results for signaling in bayesian zero sum and network routing games"

Connected through hyperedge HE-3 (induced by source paper "settling the complexity of computing approximate two player nash equilibria"):
  with members:
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "approximating nash equilibria in tree polymatrix games"
    - "the query complexity of correlated equilibria"
    - "communication complexity of approximate nash equilibria"
    - "inapproximability results for approximate nash equilibria"
    - "well supported versus approximate nash equilibria query complexity of large games"
    - "near optimal hardness results for signaling in bayesian games"
    - "eth hardness for densest k subgraph with perfect completeness"

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)