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 "simple dynamic algorithms for maximal independent set and other problems"):
  Abstract: Most graphs in real life keep changing with time. These changes can be in the form of insertion or deletion of edges or vertices. Such rapidly changing graphs motivate us to study dynamic graph algorithms. However, three important graph problems that are perhaps not sufficiently addressed in the literature include independent sets, maximum matching (exact) and maximum flows. #R##N#Maximal Independent Set (MIS) is one of the most prominently studied problems in the distributed setting. Recently, the first dynamic MIS algorithm for distributed networks was given by Censor-Hillel et al. [PODC16], requiring expected $O(1)$ amortized rounds with $O(\Delta)$ messages per update, where $\Delta$ is the maximum degree of a vertex in the graph. They suggested an open problem to maintain MIS in fully dynamic centralized setting more efficiently. Assadi et al. [STOC18] presented a deterministic centralized fully dynamic MIS algorithm requiring $O(\min\{\Delta,m^{3/4}\})$ amortized time per update. This result is quite complex involving an exhaustive case analysis. We report a surprisingly simple deterministic centralized algorithm which improves the amortized update time to $O(\min\{\Delta,m^{2/3}\})$. #R##N#Additionally, we present some other minor results related to dynamic MIS, Maximum Flow, and Maximum Matching. A common trait of all our results is that despite improving state of the art upper bounds or matching state of the art lower bounds, they are surprisingly simple and are analysed using simple amortization arguments. Further, they use no complicated data structures or black box algorithms for their implementation.

Includes members:
  Member "fully dynamic mis in uniformly sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "explicit and implicit dynamic coloring of graphs with bounded arboricity")
  Member "fully dynamic maximal independent set with sublinear update time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "dynamic minimum spanning forest with subpolynomial worst case update time":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")
  Member "fully dynamic maximal matching in constant update time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")
  Member "on the hardness of partially dynamic graph problems and connections to diameter":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "rounding dynamic matchings against an adaptive adversary")
  Member "feedback from nature simple randomised distributed algorithms for maximal independent set selection and greedy colouring":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed voting in beep model")
  Member "an improved distributed algorithm for maximal independent set":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")

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.DS(Data Structures and Algorithms)