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: "convergence of distributed randomized pagerank algorithms"
  Abstract: The PageRank algorithm employed by Google quantifies the importance of each page by the link structure of the web. To reduce the computational burden the distributed randomized PageRank algorithms (DRPA) recently appeared in literature suggest pages to update their ranking values by locally communicating with the linked pages. The main objective of the note is to show that the estimates generated by DRPA converge to the true PageRank value almost surely under the assumption that the randomization is realized in an independent and identically distributed (iid) way. This is achieved with the help of the stochastic approximation (SA) and its convergence results.

Connected through hyperedge HE-1 (induced by source paper "distributed algorithms for computation of centrality measures in complex networks"):
  with members:
    - "stability and continuity of centrality measures in weighted graphs"
    - "ergodic randomized algorithms and dynamics over networks"
    - "axioms for centrality"
    - "explicit convergence rate of a distributed alternating direction method of multipliers"
    - "distributed randomized algorithms for the pagerank computation"
    - "fundamentals of large sensor networks connectivity capacity clocks and computation"

Connected through hyperedge HE-2 (induced by source paper "ergodic randomized algorithms and dynamics over networks"):
  with members:
    - "pagerank optimization by edge selection"
    - "almost sure convergence of a randomized algorithm for relative localization in sensor networks"
    - "gossips and prejudices ergodic randomized dynamics in social networks"
    - "limited benefit of cooperation in distributed relative localization"
    - "opinion fluctuations and disagreement in social networks"
    - "distributed randomized algorithms for the pagerank computation"
    - "a web aggregation approach for distributed randomized pagerank algorithms"
    - "error scaling laws for linear optimal estimation from relative measurements"

Connected through hyperedge HE-3 (induced by source paper "the pagerank problem multi agent consensus and web aggregation a systems and control viewpoint"):
  with members:
    - "pagerank optimization by edge selection"
    - "distributed randomized algorithms for the pagerank computation"
    - "a web aggregation approach for distributed randomized pagerank algorithms"
    - "pagerank standing on the shoulders of giants"
    - "co authorship networks in the digital library research community"

Connected through hyperedge HE-4 (induced by source paper "reinforcement learning for matrix computations pagerank as an example"):
  with members:
    - "distributed randomized algorithms for the pagerank computation"

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.SY(Systems and Control)