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 "metric embedding via shortest path decompositions"):
  Abstract: We study the problem of embedding weighted graphs of pathwidth $k$ into $\ell_p$ spaces. Our main result is an $O(k^{\min\{\nicefrac{1}{p},\nicefrac{1}{2}\}})$-distortion embedding. For $p=1$, this is a super-exponential improvement over the best previous bound of Lee and Sidiropoulos. Our distortion bound is asymptotically tight for any fixed $p >1$. #R##N#Our result is obtained via a novel embedding technique that is based on low depth decompositions of a graph via shortest paths. The core new idea is that given a geodesic shortest path $P$, we can probabilistically embed all points into 2 dimensions with respect to $P$. For $p>2$ our embedding also implies improved distortion on bounded treewidth graphs ($O((k\log n)^{\nicefrac{1}{p}})$). For asymptotically large $p$, our results also implies improved distortion on graphs excluding a minor.

Includes members:
  Member "metric decompositions of path separable graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scattering and sparse partitions and their applications")
  Member "cops robbers and threatening skeletons padded decomposition for minor free graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scattering and sparse partitions and their applications")
  Member "sparsest cut on bounded treewidth graphs algorithms and hardness results":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the parameterized complexity of sparsest cut and small set expansion problems")
  Member "measured descent a new embedding method for finite metrics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "scattering and sparse partitions and their applications")

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)