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: "iterative approximate consensus in the presence of byzantine link failures"
  Abstract: This paper explores the problem of reaching approximate consensus in synchronous point-to-point networks, where each directed link of the underlying communication graph represents a communication channel between a pair of nodes. We adopt the transient Byzantine link failure model [15, 16], where an omniscient adversary controls a subset of the directed communication links, but the nodes are assumed to be fault-free. #R##N#Recent work has addressed the problem of reaching approximate consen- sus in incomplete graphs with Byzantine nodes using a restricted class of iterative algorithms that maintain only a small amount of memory across iterations [22, 21, 23, 12]. However, to the best of our knowledge, we are the first to consider approximate consensus in the presence of Byzan- tine links. We extend our past work that provided exact characterization of graphs in which the iterative approximate consensus problem in the presence of Byzantine node failures is solvable [22, 21]. In particular, we prove a tight necessary and sufficient condition on the underlying com- munication graph for the existence of iterative approximate consensus algorithms under transient Byzantine link model. The condition answers (part of) the open problem stated in [16].

Connected through hyperedge HE-1 (induced by source paper "an improved approximate consensus algorithm in the presence of mobile faults"):
  with members:
    - "approximate agreement under mobile byzantine faults"
    - "iterative approximate byzantine consensus in arbitrary directed graphs"

Connected through hyperedge HE-2 (induced by source paper "recent results on fault tolerant consensus in message passing networks"):
  with members:
    - "xft practical fault tolerance beyond crashes"
    - "gracefully degrading consensus and k set agreement in directed dynamic networks"
    - "approximate consensus in highly dynamic networks the role of averaging algorithms"
    - "asynchronous convex consensus in the presence of crash faults"
    - "reaching approximate byzantine consensus with multi hop communication"
    - "byzantine vector consensus in complete graphs"
    - "iterative byzantine vector consensus in incomplete graphs"
    - "paxoslease diskless paxos for leases"

Connected through hyperedge HE-3 (induced by source paper "approximate agreement under mobile byzantine faults"):
  with members:
    - "approximate consensus in highly dynamic networks the role of averaging algorithms"
    - "asynchronous convex consensus in the presence of crash faults"
    - "reaching approximate byzantine consensus with multi hop communication"
    - "iterative approximate byzantine consensus under a generalized fault model"
    - "iterative approximate byzantine consensus in arbitrary directed graphs"

Connected through hyperedge HE-4 (induced by source paper "reaching approximate byzantine consensus with multi hop communication"):
  with members:
    - "iterative byzantine vector consensus in incomplete graphs"
    - "consensus of multi agent networks in the presence of adversaries using only local information"
    - "matrix representation of iterative approximate byzantine consensus in directed graphs"
    - "iterative approximate byzantine consensus in arbitrary directed graphs"
    - "distributed algorithms for consensus and coordination in the presence of packet dropping communication links part ii coefficients of ergodicity analysis approach"
    - "robustness of information diffusion algorithms to locally bounded adversaries"
    - "simple gradecast based algorithms"

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)