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: "tight bounds for rumor spreading with vertex expansion"
  Abstract: We establish a bound for the classic PUSH-PULL rumor spreading protocol on arbitrary graphs, in terms of the vertex expansion of the graph. We show that O(log^2(n)/\alpha) rounds suffice with high probability to spread a rumor from a single node to all n nodes, in any graph with vertex expansion at least \alpha. This bound matches the known lower bound, and settles the question on the relationship between rumor spreading and vertex expansion asked by Chierichetti, Lattanzi, and Panconesi (SODA 2010). Further, some of the arguments used in the proof may be of independent interest, as they give new insights, for example, on how to choose a small set of nodes in which to plant the rumor initially, to guarantee fast rumor spreading.

Connected through hyperedge HE-1 (induced by source paper "the capacity of smartphone peer to peer networks"):
  with members:
    - "random gossip processes in smartphone peer to peer networks"
    - "how to discreetly spread a rumor in a crowd"
    - "rumor spreading with bounded in degree"
    - "multi message broadcast with abstract mac layers and unreliable links"
    - "faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms"

Connected through hyperedge HE-2 (induced by source paper "random gossip processes in smartphone peer to peer networks"):
  with members:
    - "gossip in a smartphone peer to peer network"
    - "how to discreetly spread a rumor in a crowd"
    - "energy efficient resource allocation for device to device underlay communication"

Connected through hyperedge HE-3 (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-4 (induced by source paper "finding optimal sinks for random walkers in a network"):
  with members:
    - "fast semidifferential based submodular function optimization"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"

Connected through hyperedge HE-5 (induced by source paper "gossip in a smartphone peer to peer network"):
  with members:
    - "how to discreetly spread a rumor in a crowd"
    - "rumor spreading with bounded in degree"

Connected through hyperedge HE-6 (induced by source paper "pull and push pull in random evolving graphs"):
  with members:
    - "rumor spreading with bounded in degree"

Connected through hyperedge HE-7 (induced by source paper "how to discreetly spread a rumor in a crowd"):
  with members:
    - "rumor spreading with bounded in degree"

Connected through hyperedge HE-8 (induced by source paper "expanders via local edge flips"):
  with members:
    - "spectral sparsification and regret minimization beyond matrix multiplicative updates"
    - "the switch markov chain for sampling irregular graphs"
    - "improved cheeger s inequality analysis of spectral partitioning algorithms through higher order spectral gap"
    - "tight bounds for randomized load balancing on arbitrary network topologies"
    - "simple fast and deterministic gossip and rumor spreading"
    - "dex self healing expanders"
    - "twice ramanujan sparsifiers"

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)