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 "minor excluded network families admit fast distributed algorithms"):
  Abstract: Distributed network optimization algorithms, such as minimum spanning tree, minimum cut, and shortest path, are an active research area in distributed computing. This paper presents a fast distributed algorithm for such problems in the CONGEST model, on networks that exclude a fixed minor. #R##N#On general graphs, many optimization problems, including the ones mentioned above, require $\tilde\Omega(\sqrt n)$ rounds of communication in the CONGEST model, even if the network graph has a much smaller diameter. Naturally, the next step in algorithm design is to design efficient algorithms which bypass this lower bound on a restricted class of graphs. Currently, the only known method of doing so uses the low-congestion shortcut framework of Ghaffari and Haeupler [SODA'16]. Building off of their work, this paper proves that excluded minor graphs admit high-quality shortcuts, leading to an $\tilde O(D^2)$ round algorithm for the aforementioned problems, where $D$ is the diameter of the network graph. To work with excluded minor graph families, we utilize the Graph Structure Theorem of Robertson and Seymour. To the best of our knowledge, this is the first time the Graph Structure Theorem has been used for an algorithmic result in the distributed setting. #R##N#Even though the proof is involved, merely showing the existence of good shortcuts is sufficient to obtain simple, efficient distributed algorithms. In particular, the shortcut framework can efficiently construct near-optimal shortcuts and then use them to solve the optimization problems. This, combined with the very general family of excluded minor graphs, which includes most other important graph classes, makes this result of significant interest.

Includes members:
  Member "distributed exact shortest paths in sublinear time":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed edge connectivity in sublinear time")
  Member "distributed exact weighted all pairs shortest paths in tilde o n 5 4 rounds":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed edge connectivity in sublinear time")
  Member "a simple deterministic distributed mst algorithm with near optimal time and message complexities":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improved algorithm for min cuts in distributed networks")
  Member "low congestion shortcuts without embedding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "near optimal schedules for simultaneous multicasts")
  Member "an almost tight distributed algorithm for computing single source shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parallel approximate undirected shortest paths via low hop emulators")
  Member "near optimal distributed maximum flow":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hardness of distributed optimization")
  Member "fast partial distance estimation and applications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fast approximate shortest paths in the congested clique")
  Member "almost tight distributed minimum cut algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "improved algorithm for min cuts in distributed networks")

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)