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: "fast and simple deterministic algorithms for highly dynamic networks"
  Abstract: This paper provides a surprisingly simple method for obtaining fast (constant amortized time) deterministic distributed algorithms for a highly-dynamic setting, in which arbitrarily many edge changes may occur in each round. Among the implications of our results are deterministic algorithms that maintain solutions to many problems, including $(degree+1)$-coloring, maximal matching, maximal independent set and the seemingly unrelated problem of a 2-approximation for minimum weight vertex cover (2-MWVC). #R##N#These significantly improve upon prior work in various aspects, such as having $O(1)$ amortized round complexity, using message of logarithmic size only, handling arbitrarily many concurrent topology changes, being deterministic, having correctness guarantees for intermediate rounds, and more. #R##N#The core of our work is in defining a subclass of locally-checkable labelings which we call locally-fixable labelings (LFLs). Very roughly speaking, these are labelings that allow a node to fix its neighborhood based solely on their old labels. We present a simple algorithm for LFLs with small labels, which handles multiple edge insertions/deletions while keeping the amortized round complexity at a small constant. We then extend it, for specific tasks, to handle the insertion and deletion of nodes. Moreover, we show that the same approach can also fix labeling with large labels, given that they can be made to behave as small labels.

Connected through hyperedge HE-1 (induced by source paper "distributed detection of cliques in dynamic networks"):
  with members:
    - "simple dynamic algorithms for maximal independent set and other problems"
    - "fully dynamic maximal independent set with sublinear update time"
    - "local distributed algorithms in highly dynamic networks"
    - "distributed triangle detection via expander decomposition"
    - "improved algorithms for fully dynamic maximal independent set"
    - "detecting cliques in congest networks"
    - "distributed subgraph detection"
    - "fooling views a new lower bound technique for distributed computations under congestion"

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)