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 "deterministically maintaining a 2 epsilon approximate minimum vertex cover in o 1 epsilon 2 amortized update time"):
  Abstract: We consider the problem of maintaining an (approximately) minimum vertex cover in an $n$-node graph $G = (V, E)$ that is getting updated dynamically via a sequence of edge insertions/deletions. We show how to maintain a $(2+\epsilon)$-approximate minimum vertex cover, deterministically, in this setting in $O(1/\epsilon^2)$ amortized update time. #R##N#Prior to our work, the best known deterministic algorithm for maintaining a $(2+\epsilon)$-approximate minimum vertex cover was due to Bhattacharya, Henzinger and Italiano [SODA 2015]. Their algorithm has an update time of $O(\log n/\epsilon^2)$. Our result gives an exponential improvement over the update time of Bhattacharya et al., and nearly matches the performance of the randomized algorithm of Solomon [FOCS 2016] who gets an approximation ratio of $2$ and an expected amortized update time of $O(1)$. #R##N#We derive our result by analyzing, via a novel technique, a variant of the algorithm by Bhattacharya et al. We consider an idealized setting where the update time of an algorithm can take any arbitrary fractional value, and use insights from this setting to come up with an appropriate potential function. Conceptually, this framework mimics the idea of an LP-relaxation for an optimization problem. The difference is that instead of relaxing an integral objective function, we relax the update time of an algorithm itself. We believe that this technique will find further applications in the analysis of dynamic algorithms.

Includes members:
  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-1 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "dynamic matching reducing integral algorithms to approximately maximal fractional algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")
  Member "fully dynamic almost maximal matching breaking the polynomial barrier for worst case time bounds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rounding dynamic matchings against an adaptive adversary")
  Member "fully dynamic maximal matching in constant 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 "design of dynamic algorithms via primal dual method":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an improved algorithm for dynamic set cover")
  Member "fully dynamic matching in bipartite graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximating multistage matching problems")
  Member "deterministic fully dynamic data structures for vertex cover and matching":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "orienting fully dynamic graphs with worst case time bounds":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dynamic approximate shortest paths and beyond subquadratic and worst case update time")

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)