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 "the impact of communication delays on distributed consensus algorithms"):
  Abstract: We study the effect of communication delays on distributed consensus algorithms. Two ways to model delays on a network are presented. The first model assumes that each link delivers messages with a fixed (constant) amount of delay, and the second model is more realistic, allowing for i.i.d. time-varying bounded delays. In contrast to previous work studying the effects of delays on consensus algorithms, the models studied here allow for a node to receive multiple messages from the same neighbor in one iteration. The analysis of the fixed delay model shows that convergence to a consensus is guaranteed and the rate of convergence is reduced by no more than a factor O(B^2) where B is the maximum delay on any link. For the time-varying delay model we also give a convergence proof which, for row-stochastic consensus protocols, is not a trivial consequence of ergodic matrix products. In both delay models, the consensus value is no longer the average, even if the original protocol was an averaging protocol. For this reason, we propose the use of a different consensus algorithm called Push-Sum [Kempe et al. 2003]. We model delays in the Push-Sum framework and show that convergence to the average consensus is guaranteed. This suggests that Push-Sum might be a better choice from a practical standpoint.

Includes members:
  Member "gossip algorithms for distributed signal processing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "inverse graph learning over optimization networks")
  Member "on asymptotic consensus value in directed random networks":
    also connected through other hyperedges:
      (none)

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)