human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "efficient k party voting with two choices"
  Abstract: We consider the problem of distributed $k$-party voting with two choices as well as a simple modification of this protocol in complete graphs. In the standard version, we are given a graph in which every node possesses one of $k$ different opinions at the beginning. In each step, every node chooses two neighbors uniformly at random. If the opinions of the two neighbors coincide, then this opinion is adopted. It is known that if $k=2$ and the difference between the two opinions is $\Omega(\sqrt{n \log n})$, then after $\mathcal{O}(\log n)$ steps, every node will possess the largest initial opinion, with high probability. #R##N#We show that if $k =\mathcal{O}(n^\epsilon)$ for some small $\epsilon$, then this protocol converges to the initial majority within $\mathcal{O}(k\log{n})$ steps, with high probability, as long as the initial difference between the largest and second largest opinion is $\Omega(\sqrt{n \log n})$. Furthermore, there exist initial configurations where the $\Theta(k)$ bound on the run time is matched. If the initial difference is $\mathcal{O}(\sqrt{n})$, then the largest opinion may loose the vote with constant probability. To speed up our process, we consider the following variant of the two-choices protocol. The process is divided into several phases, and in the first step of a phase every node applies the two choices protocol. If a new opinion is adopted, the node remembers it by setting a certain bit to true. In the subsequent steps of that phase, each node samples one neighbor, and if the bit of this neighbor is set to true, then the node takes the opinion of this neighbor and sets its bit to true as well. At the end of the phase, the bits are reset to false. Then, the phases are repeated several times. We show that this modified protocol improves significantly over the standard two-choices protocol.

Connected through hyperedge HE-1 (induced by source paper "noidy conmunixatipn on the convergence of the averaging population protocol"):
  with members:
    - "almost logarithmic time space optimal leader election in population protocols"
    - "fast space optimal leader election in population protocols"
    - "erasure correction for noisy radio networks"
    - "limits for rumor spreading in stochastic populations"
    - "ignore or comply on breaking symmetry in consensus"
    - "broadcasting in noisy radio networks"
    - "space optimal majority in population protocols"
    - "rapid asynchronous plurality consensus"

Connected through hyperedge HE-2 (induced by source paper "ignore or comply on breaking symmetry in consensus"):
  with members:
    - "bounds on the voter model in dynamic networks"
    - "stabilizing consensus with many opinions"
    - "the power of two choices in distributed voting"
    - "plurality consensus in the gossip model"
    - "simple dynamics for plurality consensus"
    - "absorption time of the moran process"
    - "coalescing random walks and voting on connected graphs"

Connected through hyperedge HE-3 (induced by source paper "minimizing message size in stochastic communication patterns fast self stabilizing protocols with 3 bits"):
  with members:
    - "self stabilizing repeated balls into bins"
    - "efficient counting with optimal resilience"
    - "towards optimal synchronous counting"
    - "stable leader election in population protocols requires linear time"
    - "stabilizing consensus with many opinions"
    - "plurality consensus in the gossip model"
    - "breathe before speaking efficient information dissemination despite noisy limited and anonymous communication"
    - "synchronous counting and computational algorithm design"

Connected through hyperedge HE-4 (induced by source paper "bounds on the voter model in dynamic networks"):
  with members:
    - "global majority consensus by local majority polling on graphs of a given degree sequence"
    - "the power of two choices in distributed voting"
    - "absorption time of the moran process"
    - "coalescing random walks and voting on connected graphs"
    - "approximating fixation probabilities in the generalized moran process"

Question: Please tell me which class the center node 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)