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 "light spanners for snowflake metrics"):
  Abstract: A classic result in the study of spanners is the existence of light low-stretch spanners for Euclidean spaces. These spanners ahve arbitrary low stretch, and weight only a constant factor greater than that of the minimum spanning tree of the points (with dependence on the stretch and Euclidean dimention). A central open problem in this field asks whether other spaces admit low weight spanners as well - for example metric space with low intrinsic dimension - yet only a handful of results of this type are known. #R##N#In this paper, we consider snowflake metric spaces of low intrinsic dimension. The {\alpha}-snowflake of a metric (X,{\delta}) is the metric (X,${\delta}^{\alpha}$) for 0<{\alpha}<1. By utilizing an approach completely different than those used for Euclidean spaces, we demonstrate that snowflake metrics admit light spanners. Further, we show that the spanner is of diameter O($\log$n), a result not possible for Euclidean spaces. As an immediate corollary to our spanner, we obtain dramatic improvments in algorithms for the traveling salesman problem in this setting, achieving a polynomial-time approximation scheme with near-linear runtime. Along the way, we show that all ${\ell}_p$ spaces admit light spanners, a result of interest in its own right.

Includes members:
  Member "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a quasi polynomial algorithm for well spaced hyperbolic tsp")
  Member "from hierarchical partitions to hierarchical covers optimal fault tolerant spanners for doubling metrics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "truly optimal euclidean spanners")
  Member "optimal euclidean spanners really short thin and lanky":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graph spanners a tutorial review")
  Member "light spanners in bounded pathwidth graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "minor free graphs have light spanners")
  Member "an optimal time construction of euclidean sparse spanners with tiny diameter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal euclidean spanners really short thin and lanky")
  Member "shallow low and light trees and tight lower bounds for euclidean spanners":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "truly optimal euclidean spanners")
  Member "fast construction of nets in low dimensional metrics and their applications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a data dependent algorithm for querying earth mover s distance with low doubling dimension")

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)