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 "epsilon approximations and epsilon nets"):
  Abstract: The use of random samples to approximate properties of geometric configurations has been an influential idea  for both combinatorial and algorithmic purposes. This chapter considers  two related notions---$\epsilon$-approximations and $\epsilon$-nets---that capture the most important quantitative properties that one would expect from a random sample with respect to an underlying geometric configuration.

Includes members:
  Member "near optimal epsilon kernel construction and related problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal bound on the combinatorial complexity of approximating polytopes")
  Member "a size sensitive discrepancy bound for set systems of bounded primal shatter dimension":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient algorithms for discrepancy minimization in convex sets")
  Member "small strong epsilon nets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "selection lemmas for various geometric objects")
  Member "constructive discrepancy minimization by walking on the edges":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "generalised pattern matching revisited")
  Member "a unified framework for approximating and clustering data":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "approximating spectral clustering via sampling a review")
  Member "tight lower bounds for the size of epsilon nets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the epsilon t net problem")
  Member "improved approximation for guarding simple galleries from the perimeter":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the parameterized complexity of guarding almost convex polygons")
  Member "algorithms for eps approximations of terrains":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "near optimal coresets of kernel density estimates")

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.CG(Computational Geometry)