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: "determining majority in networks with local interactions and very small local memory"
  Abstract: We study here the problem of determining the majority type in an arbitrary connected network, each vertex of which has initially two possible types. The vertices may have a few additional possible states and can interact in pairs only if they share an edge. Any (population) protocol is required to stabilize in the initial majority. We first present and analyze a protocol with 4 states per vertex that always computes the initial majority value, under any fair scheduler. As we prove, this protocol is optimal, in the sense that there is no population protocol that always computes majority with fewer than 4 states per vertex. However this does not rule out the existence of a protocol with 3 states per vertex that is correct with high probability. To this end, we examine a very natural majority protocol with 3 states per vertex, introduced in [Angluin et al. 2008] where its performance has been analyzed for the clique graph. We study the performance of this protocol in arbitrary networks. We prove that, when the two initial states are put uniformly at random on the vertices, this protocol converges to the initial majority with probability higher than the probability of converging to the initial minority. In contrast, we present an infinite family of graphs, on which the protocol can fail whp, even when the difference between the initial majority and the initial minority is $n - \Theta(\ln{n})$. We also present another infinite family of graphs in which the protocol of Angluin et al. takes an expected exponential time to converge. These two negative results build upon a very positive result concerning the robustness of the protocol on the clique. Surprisingly, the resistance of the clique to failure causes the failure in general graphs. Our techniques use new domination and coupling arguments for suitably defined processes whose dynamics capture the antagonism between the states involved.

Connected through hyperedge HE-1 (induced by source paper "robust comparison in population protocols"):
  with members:
    - "majority stabilization in population protocols"
    - "fast space optimal leader election in population protocols"
    - "robust detection in leak prone population protocols"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "passively mobile communicating machines that use restricted space"
    - "the computational power of population protocols"

Connected through hyperedge HE-2 (induced by source paper "the power of global knowledge on self stabilizing population protocols"):
  with members:
    - "almost logarithmic time space optimal leader election in population protocols"

Connected through hyperedge HE-3 (induced by source paper "communication cost of consensus for nodes with limited memory"):
  with members:
    - "global majority consensus by local majority polling on graphs of a given degree sequence"
    - "population protocols are fast"
    - "population protocols for leader election and exact majority with o log 2 n states and o log 2 n convergence time"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "discordant voting processes on finite graphs"
    - "stable leader election in population protocols requires linear time"
    - "plurality consensus in the gossip model"

Connected through hyperedge HE-4 (induced by source paper "on counting the population size"):
  with members:
    - "exact size counting in uniform population protocols in nearly logarithmic time"
    - "efficient size estimation and impossibility of termination in uniform dense population protocols"
    - "fast space optimal leader election in population protocols"
    - "simple load balancing"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "stable leader election in population protocols requires linear time"
    - "the computational power of population protocols"

Connected through hyperedge HE-5 (induced by source paper "on the necessary memory to compute the plurality in multi agent systems"):
  with members:
    - "distributed voting ranking with optimal number of states per node"
    - "tight analysis for the 3 majority consensus dynamics"
    - "time and space optimal counting in population protocols"
    - "stabilizing consensus with many opinions"
    - "plurality consensus in the gossip model"
    - "timing in chemical reaction networks"
    - "the computational power of population protocols"

Connected through hyperedge HE-6 (induced by source paper "distributed community detection via metastability of the 2 choices dynamics"):
  with members:
    - "pooling or sampling collective dynamics for electrical flow estimation"
    - "phase transition of the 2 choices dynamics on core periphery networks"
    - "the ants problem"
    - "limits for rumor spreading in stochastic populations"
    - "ignore or comply on breaking symmetry in consensus"
    - "distributed graph clustering and sparsification"
    - "average whenever you meet opportunistic protocols for community detection"
    - "a tight analysis of the parallel undecided state dynamics with two colors"

Connected through hyperedge HE-7 (induced by source paper "consensus needs broadcast in noiseless models but can be exponentially easier in the presence of noise"):
  with members:
    - "ignore or comply on breaking symmetry in consensus"
    - "tight analysis for the 3 majority consensus dynamics"
    - "a tight analysis of the parallel undecided state dynamics with two colors"
    - "distributed computing with channel noise"
    - "breaking the log n barrier on rumor spreading"
    - "stabilizing consensus with many opinions"
    - "noisy rumor spreading and plurality consensus"
    - "the power of two choices in distributed voting"

Connected through hyperedge HE-8 (induced by source paper "almost logarithmic time space optimal leader election in population protocols"):
  with members:
    - "fast space optimal leader election in population protocols"
    - "logarithmic expected time leader election in population protocol model"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "time vs information tradeoffs for leader election in anonymous trees"
    - "on convergence and threshold properties of discrete lotka volterra population protocols"
    - "stable leader election in population protocols requires linear time"
    - "plurality consensus in the gossip model"

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)