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 "independent set induced matching and pricing connections and tight subexponential time approximation hardnesses"):
  Abstract: We present a series of almost settled inapproximability results for three fundamental problems. The first in our series is the subexponential-time inapproximability of the maximum independent set problem, a question studied in the area of parameterized complexity. The second is the hardness of approximating the maximum induced matching problem on bounded-degree bipartite graphs. The last in our series is the tight hardness of approximating the k-hypergraph pricing problem, a fundamental problem arising from the area of algorithmic game theory. In particular, assuming the Exponential Time Hypothesis, our two main results are: #R##N#- For any r larger than some constant, any r-approximation algorithm for the maximum independent set problem must run in at least 2^{n^{1-\epsilon}/r^{1+\epsilon}} time. This nearly matches the upper bound of 2^{n/r} (Cygan et al., 2008). It also improves some hardness results in the domain of parameterized complexity (e.g., Escoffier et al., 2012 and Chitnis et al., 2013) #R##N#- For any k larger than some constant, there is no polynomial time min (k^{1-\epsilon}, n^{1/2-\epsilon})-approximation algorithm for the k-hypergraph pricing problem, where n is the number of vertices in an input graph. This almost matches the upper bound of min (O(k), \tilde O(\sqrt{n})) (by Balcan and Blum, 2007 and an algorithm in this paper). #R##N#We note an interesting fact that, in contrast to n^{1/2-\epsilon} hardness for polynomial-time algorithms, the k-hypergraph pricing problem admits n^{\delta} approximation for any \delta >0 in quasi-polynomial time. This puts this problem in a rare approximability class in which approximability thresholds can be improved significantly by allowing algorithms to run in quasi-polynomial time.

Includes members:
  Member "completely inapproximable monotone and antimonotone parameterized problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parameterized inapproximability for steiner orientation by gap amplification")
  Member "on problems as hard as cnf sat":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "fixed parameter and approximation algorithms a new look":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parameterized approximation algorithms for directed steiner network problems")
  Member "graph pricing problem on bounded treewidth bounded genus and k partite graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hardness of graph pricing through generalized max dicut")
  Member "subexponential and fpt time inapproximability of independent set and related problems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fixed parameter inapproximability for clique and setcover in time super exponential in opt")
  Member "graph products revisited tight approximation hardness of induced matching poset dimension and more":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spanning trees with edge conflicts and wireless connectivity")
  Member "algorithmic pricing via virtual valuations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "simple credible and approximately optimal auctions")
  Member "exponential time approximation of hard problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "improved in approximability bounds for d scattered set")

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)