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 "sometimes reliable spanners of almost linear size"):
  Abstract: Reliable spanners can withstand huge failures, even when a linear number of vertices are deleted from the network. In case of failures, a reliable spanner may have some additional vertices for which the spanner property no longer holds, but this collateral damage is bounded by a fraction of the size of the attack. It is known that $\Omega(n\log n)$ edges are needed to achieve this strong property, where $n$ is the number of vertices in the network, even in one dimension. Constructions of reliable geometric $(1+\varepsilon)$-spanners, for $n$ points in $\Re^d$, are known, where the resulting graph has $O( n \log n \log \log^{6}n )$ edges. #R##N#Here, we show randomized constructions of smaller size spanners that have the desired reliability property in expectation or with good probability. The new construction is simple, and potentially practical -- replacing a hierarchical usage of expanders (which renders the previous constructions impractical) by a simple skip-list like construction. This results in a $1$-spanner, on the line, that has linear number of edges. Using this, we present a construction of a reliable spanner in $\Re^d$ with $O( n \log \log^{2} n \log \log \log n )$ edges.

Includes members:
  Member "a spanner for the day after":
    also connected through other hyperedges:
      (none)
  Member "on locality sensitive orderings and their applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a spanner for the day after")
  Member "near optimal o k robust geometric spanners":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a spanner for the day after")
  Member "robust geometric spanners":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "piecewise linear regressions for approximating distance metrics")

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)