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 "near isometric terminal embeddings for doubling metrics"):
  Abstract: Given a metric space $(X,d)$, a set of terminals $K\subseteq X$, and a parameter $t\ge 1$, we consider metric structures (e.g., spanners, distance oracles, embedding into normed spaces) that preserve distances for all pairs in $K\times X$ up to a factor of $t$, and have small size (e.g. number of edges for spanners, dimension for embeddings). While such terminal (aka source-wise) metric structures are known to exist in several settings, no terminal spanner or embedding with distortion close to 1, i.e., $t=1+\epsilon$ for some small $0<\epsilon<1$, is currently known. #R##N#Here we devise such terminal metric structures for {\em doubling} metrics, and show that essentially any metric structure with distortion $1+\epsilon$ and size $s(|X|)$ has its terminal counterpart, with distortion $1+O(\epsilon)$ and size $s(|K|)+1$. In particular, for any doubling metric on $n$ points, a set of $k=o(n)$ terminals, and constant $0<\epsilon<1$, there exists: #R##N#(1) A spanner with stretch $1+\epsilon$ for pairs in $K\times X$, with $n+o(n)$ edges. #R##N#(2) A labeling scheme with stretch $1+\epsilon$ for pairs in $K\times X$, with label size $\approx \log k$. #R##N#(3) An embedding into $\ell_\infty^d$ with distortion $1+\epsilon$ for pairs in $K\times X$, where $d=O(\log k)$. #R##N#Moreover, surprisingly, the last two results apply if only $K$ is a doubling metric, while $X$ can be arbitrary.

Includes members:
  Member "reachability preservers new extremal bounds and approximation algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "some general structure for extremal sparsification problems")
  Member "a light metric spanner":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the edge crossings of the greedy spanner")
  Member "prioritized metric structures and embedding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "scattering and sparse partitions and their applications")
  Member "on pairwise spanners":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "weighted additive spanners")
  Member "optimal euclidean spanners really short thin and lanky":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "graph spanners a tutorial review")
  Member "ramsey partitions and proximity data structures":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "labelings vs embeddings on distributed representations of distances")
  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.DS(Data Structures and Algorithms)