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 "exponentially faster shortest paths in the congested clique"):
  Abstract: We present improved deterministic algorithms for approximating shortest paths in the Congested Clique model of distributed computing. We obtain $poly(\log\log n)$-round algorithms for the following problems in unweighted undirected $n$-vertex graphs: #R##N#-- $(1+\epsilon)$-approximation of multi-source shortest paths (MSSP) from $O(\sqrt{n})$ sources. #R##N#-- $(2+\epsilon)$-approximation of all pairs shortest paths (APSP). #R##N#-- $(1+\epsilon,\beta)$-approximation of APSP where $\beta=O(\frac{\log\log n}{\epsilon})^{\log\log n}$. #R##N#These bounds improve exponentially over the state-of-the-art poly-logarithmic bounds due to [Censor-Hillel et al., PODC19]. It also provides the first nearly-additive bounds for the APSP problem in sub-polynomial time. Our approach is based on distinguishing between short and long distances based on some distance threshold $t = O(\frac{\beta}{\epsilon})$ where $\beta=O(\frac{\log\log n}{\epsilon})^{\log\log n}$. Handling the long distances is done by devising a new algorithm for computing sparse $(1+\epsilon,\beta)$ emulator with $O(n\log\log n)$ edges. For the short distances, we provide distance-sensitive variants for the distance tool-kit of [Censor-Hillel et al., PODC19]. By exploiting the fact that this tool-kit should be applied only on local balls of radius $t$, their round complexities get improved from $poly(\log n)$ to $poly(\log t)$. #R##N#Finally, our deterministic solutions for these problems are based on a derandomization scheme of a novel variant of the hitting set problem, which might be of independent interest.

Includes members:
  Member "near additive spanners and near exact hopsets a unified view":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graph spanners a tutorial review")
  Member "near additive spanners in low polynomial deterministic congest time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "graph spanners a tutorial review")
  Member "fast approximate shortest paths in the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parallel approximate undirected shortest paths via low hop emulators")
  Member "congested clique algorithms for graph spanners":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "massively parallel algorithms for distance approximation and spanners")
  Member "sparse matrix multiplication and triangle listing in the congested clique model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fast approximate shortest paths in the congested clique")
  Member "linear size hopsets with small hopbound and distributed routing with low memory":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fast approximate shortest paths in the congested clique")
  Member "thorup zwick emulators are universally optimal hopsets":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deterministic algorithms for decremental approximate shortest paths faster and simpler")
  Member "towards a complexity theory for the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")

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)