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 "sparsification and subexponential approximation"):
  Abstract: Instance sparsification is well-known in the world of exact computation since it is very closely linked to the Exponential Time Hypothesis. In this paper, we extend the concept of sparsification in order to capture subexponential time approximation. We develop a new tool for inapproximability, called approximation preserving sparsification and use it in order to get strong inapproximability results in subexponential time for several fundamental optimization problems as Max Independent Set, Min Dominating Set, Min Feedback Vertex Set, and Min Set Cover.

Includes members:
  Member "multi parameter complexity analysis for constrained size graph problems using greediness for parameterization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parameterized algorithms for graph partitioning problems")
  Member "fixed parameter and approximation algorithms a new look":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parameterized approximation algorithms for directed steiner network problems")
  Member "independent set induced matching and pricing connections and tight subexponential time approximation hardnesses":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "revenue maximization for query pricing")
  Member "an exponential time 2 approximation algorithm for bandwidth":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "subexponential and fpt time inapproximability of independent set and related problems")
  Member "exponential time approximation of hard problems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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)