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 "push sum with transmission failures"):
  Abstract: The push-sum algorithm allows distributed computing of the average on a directed graph, and is particularly relevant when one is restricted to one-way and/or asynchronous communications. We investigate its behavior in the presence of unreliable communication channels where messages can be lost. We show that convergence still holds, and analyze the error of the final common value we get for the essential case of two nodes, both theoretically and numerically. We compare this error performance with that of the standard consensus algorithm. For the multi-node case, we deduce fundamental properties that implicitly describe the distribution of the final value obtained.

Includes members:
  Member "analysis of sum weight like algorithms for averaging in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sample greedy gossip distributed kalman filter")
  Member "average consensus on general strongly connected digraphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed nesterov gradient methods over arbitrary graphs")
  Member "gossip algorithms for distributed signal processing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "inverse graph learning over optimization networks")
  Member "distributed consensus algorithms in sensor networks quantized data and random link failures":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fully decentralized multi agent reinforcement learning with networked agents")

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)