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: "discordant voting processes on finite graphs"
  Abstract: We consider an asynchronous voting process on graphs which we call discordant voting, and which can be described as follows. Initially each vertex holds one of two opinions, red or blue say. Neighbouring vertices with different opinions interact pairwise. After an interaction both vertices have the same colour. The quantity of interest is T, the time to reach consensus , i.e. the number of interactions needed for all vertices have the same colour. #R##N#An edge whose endpoint colours differ (i.e. one vertex is coloured red and the other one blue) is said to be discordant. A vertex is discordant if its is incident with a discordant edge. In discordant voting, all interactions are based on discordant edges. Because the voting process is asynchronous there are several ways to update the colours of the interacting vertices. Push: Pick a random discordant vertex and push its colour to a random discordant neighbour. Pull: Pick a random discordant vertex and pull the colour of a random discordant neighbour. Oblivious: Pick a random endpoint of a random discordant edge and push the colour to the other end point. #R##N#We show that E(T), the expected time to reach consensus, depends strongly on the underlying graph and the update rule. For connected graphs on n vertices, and an initial half red, half blue colouring the following hold. For oblivious voting, E(T) =n^2/4 independent of the underlying graph. For the complete graph K_n, the push protocol has E(T)= Theta(n log(n)), whereas the pull protocol has E(T)= Theta(2^n). For the cycle C_n all three protocols have E(T) = Theta(n^2). For the star graph however, the pull protocol has E(T)=O(n^2), whereas the push protocol is slower with E(T) = Theta(n^2 log(n)). #R##N#The wide variation in E(T) for the pull protocol is to be contrasted with the well known model of synchronous pull voting, for which E(T) = O(n) on many classes of expanders.

Connected through hyperedge HE-1 (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"
    - "stable leader election in population protocols requires linear time"
    - "plurality consensus in the gossip model"
    - "determining majority in networks with local interactions and very small local memory"

Connected through hyperedge HE-2 (induced by source paper "phase transition of the 2 choices dynamics on core periphery networks"):
  with members:
    - "tight analysis for the 3 majority consensus dynamics"
    - "the coalescing branching random walk on expanders and the dual epidemic process"
    - "bounds on the voter model in dynamic networks"
    - "fast plurality consensus in regular expanders"
    - "stabilizing consensus with many opinions"
    - "core periphery in networks an axiomatic approach"
    - "the power of two choices in distributed voting"
    - "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.DM(Discrete Mathematics)