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: "fully dynamic maximal independent set with polylogarithmic update time"
  Abstract: We present the first algorithm for maintaining a maximal independent set (MIS) of a fully dynamic graph---which undergoes both edge insertions and deletions---in polylogarithmic time. Our algorithm is randomized and, per update, takes $O(\log^2 \Delta \cdot \log^2 n)$ expected time. Furthermore, the algorithm can be adjusted to have $O(\log^2 \Delta \cdot \log^4 n)$ worst-case update-time with high probability. Here, $n$ denotes the number of vertices and $\Delta$ is the maximum degree in the graph. #R##N#The MIS problem in fully dynamic graphs has attracted significant attention after a breakthrough result of Assadi, Onak, Schieber, and Solomon [STOC'18] who presented an algorithm with $O(m^{3/4})$ update-time (and thus broke the natural $\Omega(m)$ barrier) where $m$ denotes the number of edges in the graph. This result was improved in a series of subsequent papers, though, the update-time remained polynomial. In particular, the fastest algorithm prior to our work had $\widetilde{O}(\min\{\sqrt{n}, m^{1/3}\})$ update-time [Assadi et al. SODA'19]. #R##N#Our algorithm maintains the lexicographically first MIS over a random order of the vertices. As a result, the same algorithm also maintains a 3-approximation of correlation clustering. We also show that a simpler variant of our algorithm can be used to maintain a random-order lexicographically first maximal matching in the same update-time.

Connected through hyperedge HE-1 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model"):
  with members:
    - "how fast can you update your mst dynamic algorithms for cluster computing"
    - "batch dynamic algorithms via parallel change propagation and applications to dynamic trees"
    - "parallel batch dynamic graph connectivity"
    - "dynamic algorithms for the massively parallel computation model"
    - "fully dynamic maximal independent set in expected poly log update time"
    - "a deterministic algorithm for the mst problem in constant rounds of congested clique"
    - "exponentially faster massively parallel maximal matching"
    - "parallel batch dynamic graphs algorithms and lower bounds"

Connected through hyperedge HE-2 (induced by source paper "independent sets of dynamic rectangles algorithms and experiments"):
  with members:
    - "online matching with general arrivals"
    - "fully dynamic maximal independent set in expected poly log update time"
    - "exploring semi automatic map labeling"
    - "fully dynamic maximal independent set with sublinear update time"
    - "a deamortization approach for dynamic spanner and dynamic maximal matching"
    - "dynamic algorithms for graph coloring"
    - "on approximating maximum independent set of rectangles"
    - "interval scheduling and colorful independent sets"

Connected through hyperedge HE-3 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism"):
  with members:
    - "storing and querying large scale spatio temporal graphs with high throughput edge insertions"
    - "parallel batch dynamic graph connectivity"
    - "demystifying graph databases analysis and taxonomy of data organization system designs and graph queries"
    - "graph processing on fpgas taxonomy survey challenges"
    - "slim fly a cost effective low diameter network topology"
    - "red blue pebbling revisited near optimal parallel matrix matrix multiplication"
    - "dynamic algorithms for the massively parallel computation model"
    - "fatpaths routing in supercomputers data centers and clouds with low diameter networks when shortest paths fall short"

Connected through hyperedge HE-4 (induced by source paper "fully dynamic δ 1 coloring in constant update time"):
  with members:
    - "constant time dynamic delta 1 coloring and weight approximation for minimum spanning forest dynamic algorithms meet property testing"
    - "fully dynamic maximal independent set in expected poly log update time"
    - "fully dynamic mis in uniformly sparse graphs"
    - "fully dynamic maximal independent set with sublinear update time"
    - "dynamic algorithms for graph coloring"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "fully dynamic maximal matching in constant update time"
    - "fully dynamic maximal matching in o log n update time"

Connected through hyperedge HE-5 (induced by source paper "fully dynamic maximal independent set in expected poly log update time"):
  with members:
    - "simple dynamic algorithms for maximal independent set and other problems"
    - "fully dynamic mis in uniformly sparse graphs"
    - "fully dynamic maximal independent set with sublinear update time"
    - "improved algorithms for fully dynamic maximal independent set"
    - "a deamortization approach for dynamic spanner and dynamic maximal matching"
    - "optimal dynamic distributed mis"

Connected through hyperedge HE-6 (induced by source paper "fully dynamic mis in uniformly sparse graphs"):
  with members:
    - "fully dynamic maximal independent set in expected poly log update time"
    - "fully dynamic maximal independent set with sublinear update time"
    - "optimal dynamic distributed mis"
    - "orienting fully dynamic graphs with worst case time bounds"
    - "greedy sequential maximal independent set and matching are parallel on average"
    - "simple deterministic algorithms for fully dynamic maximal matching"

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.DS(Data Structures and Algorithms)