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 "fast distributed algorithms for connectivity and mst in large graphs"):
  Abstract: Motivated by the increasing need to understand the algorithmic foundations of distributed large-scale graph computations, we study a number of fundamental graph problems in a message-passing model for distributed computing where $k \geq 2$ machines jointly perform computations on graphs with $n$ nodes (typically, $n \gg k$). The input graph is assumed to be initially randomly partitioned among the $k$ machines, a common implementation in many real-world systems. Communication is point-to-point, and the goal is to minimize the number of communication rounds of the computation. #R##N#Our main result is an (almost) optimal distributed randomized algorithm for graph connectivity. Our algorithm runs in $\tilde{O}(n/k^2)$ rounds ($\tilde{O}$ notation hides a $\poly\log(n)$ factor and an additive $\poly\log(n)$ term). This improves over the best previously known bound of $\tilde{O}(n/k)$ [Klauck et al., SODA 2015], and is optimal (up to a polylogarithmic factor) in view of an existing lower bound of $\tilde{\Omega}(n/k^2)$. Our improved algorithm uses a bunch of techniques, including linear graph sketching, that prove useful in the design of efficient distributed graph algorithms. Using the connectivity algorithm as a building block, we then present fast randomized algorithms for computing minimum spanning trees, (approximate) min-cuts, and for many graph verification problems. All these algorithms take $\tilde{O}(n/k^2)$ rounds, and are optimal up to polylogarithmic factors. We also show an almost matching lower bound of $\tilde{\Omega}(n/k^2)$ rounds for many graph verification problems by leveraging lower bounds in random-partition communication complexity.

Includes members:
  Member "near optimal clustering in the k machine model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient distributed community detection in the stochastic block model")
  Member "tight bounds for distributed graph computations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sparse matrix multiplication with bandwidth restricted all to all communication")
  Member "on the distributed complexity of large scale graph computations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")
  Member "a time and message optimal distributed algorithm for minimum spanning trees":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improved algorithm for min cuts in distributed networks")
  Member "super fast mst algorithms in the congested clique using o m messages":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed approximation algorithms for steiner tree in the mathcal congested mathcal clique")
  Member "distributed algorithms for finding local clusters using heat kernel pagerank":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient estimation of heat kernel pagerank for local clustering")
  Member "algebraic methods in the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "construction and impromptu repair of an mst in a distributed network with o m communication":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "message reduction in the local model is a free lunch")

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.DC(Distributed, Parallel, and Cluster Computing)