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 "efficient distributed computation of mis and generalized mis in linear hypergraphs"):
  Abstract: Given a graph, a maximal independent set (MIS) is a maximal subset of pairwise non-adjacent vertices. Finding an MIS is a fundamental problem in distributed computing. Although the problem is extensively studied and well understood in simple graphs, our knowledge is still quite limited when solving it in hypergraphs, especially in the distributed CONGEST model. In this paper, we focus on linear hypergraphs---a class of hypergraphs in which any two hyperedges overlap on at most one node. #R##N#We first present a randomized algorithm for computing an MIS in linear hypergraphs. It has poly-logarithmic runtime and it works in the CONGEST model. The algorithm uses a network decomposition to achieve fast parallel processing. Within each cluster of the decomposition, we run a distributed variant of a parallel hypergraph MIS algorithm by Luczak and Szymanska. #R##N#We then propose the concept of a generalized maximal independent set (GMIS) as an extension to the classical MIS in hypergraphs. More specifically, in a GMIS, for each hyperedge $e$ in a hypergraph $\mathcal{H}$, we associate an integer threshold $t_e$ in the range $[1, |e|-1]$, and the goal is to find a maximal subset $\mathcal{I}$ of vertices that do not violate any threshold constraints: $\forall e \in E(\mathcal{H}), |e \cap \mathcal{I}| \leq t_e$. We hope that GMIS might capture a broader class of real-world problems than MIS; we also believe that GMIS is an interesting and challenging symmetry breaking problem on its own. #R##N#Our second upper bound result is a distributed algorithm for computing a GMIS in linear hypergraphs, subject to the constraint that the maximum hyperedge size is bounded by some constant. Again, the algorithm has poly-logarithmic runtime and it works in the CONGEST model. It is obtained by generalizing our previous (linear) hypergraph MIS algorithm.

Includes members:
  Member "derandomized concentration bounds for polynomials and hypergraph maximal independent set":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graph sparsification for derandomizing massively parallel computation with low space")
  Member "derandomizing local distributed algorithms under bandwidth restrictions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "on the complexity of local distributed graph problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "distributed strong diameter network decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the use of randomness in local distributed graph algorithms")
  Member "an improved distributed algorithm for maximal independent set":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")
  Member "distributed symmetry breaking in hypergraphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deterministic distributed edge coloring via hypergraph maximal matching")
  Member "on computing maximal independent sets of hypergraphs in parallel":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "derandomized concentration bounds for polynomials and hypergraph maximal independent set")
  Member "the locality of distributed symmetry breaking":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "distributed maximum matching verification in congest")

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)