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: "changing bases multistage optimization for matroids and matchings"
  Abstract: This paper is motivated by the fact that many systems need to be maintained continually while the underlying costs change over time. The challenge is to continually maintain near-optimal solutions to the underlying optimization problems, without creating too much churn in the solution itself. We model this as a multistage combinatorial optimization problem where the input is a sequence of cost functions (one for each time step); while we can change the solution from step to step, we incur an additional cost for every such change. We study the multistage matroid maintenance problem, where we need to maintain a base of a matroid in each time step under the changing cost functions and acquisition costs for adding new elements. The online version of this problem generalizes online paging. E.g., given a graph, we need to maintain a spanning tree $T_t$ at each step: we pay $c_t(T_t)$ for the cost of the tree at time $t$, and also $| T_t\setminus T_{t-1} |$ for the number of edges changed at this step. Our main result is an $O(\log m \log r)$-approximation, where $m$ is the number of elements/edges and $r$ is the rank of the matroid. We also give an $O(\log m)$ approximation for the offline version of the problem. These bounds hold when the acquisition costs are non-uniform, in which caseboth these results are the best possible unless P=NP. #R##N#We also study the perfect matching version of the problem, where we must maintain a perfect matching at each step under changing cost functions and costs for adding new elements. Surprisingly, the hardness drastically increases: for any constant $\epsilon>0$, there is no $O(n^{1-\epsilon})$-approximation to the multistage matching maintenance problem, even in the offline case.

Connected through hyperedge HE-1 (induced by source paper "multistage graph problems on a global budget"):
  with members:
    - "multistage vertex cover"
    - "temporal matching"
    - "computing maximum matchings in temporal graphs"
    - "online multistage subset maximization problems"
    - "multistage knapsack"
    - "facility location in evolving metrics"
    - "contracting graphs to paths and trees"

Connected through hyperedge HE-2 (induced by source paper "approximating multistage matching problems"):
  with members:
    - "multistage vertex cover"
    - "online multistage subset maximization problems"
    - "temporal vertex cover with a sliding time window"
    - "fully dynamic matching in bipartite graphs"

Connected through hyperedge HE-3 (induced by source paper "computing maximum matchings in temporal graphs"):
  with members:
    - "temporal matching"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "tight competitive ratios of classic matching algorithms in the fully online model"
    - "temporal vertex cover with a sliding time window"
    - "how to match when all vertices arrive online"
    - "sliding window temporal graph coloring"
    - "efficient and adaptive parameterized algorithms on modular decompositions"

Connected through hyperedge HE-4 (induced by source paper "lp based algorithms for multistage minimization problems"):
  with members:
    - "multistage vertex cover"
    - "online multistage subset maximization problems"
    - "multistage knapsack"
    - "facility location in evolving metrics"
    - "dynamic facility location via exponential clocks"
    - "the power of deferral maintaining a constant competitive steiner tree online"
    - "on the tradeoff between stability and fit"
    - "a new multilayered pcp and the hardness of hypergraph vertex cover"

Connected through hyperedge HE-5 (induced by source paper "reallocating multiple facilities on the line"):
  with members:
    - "the online k taxi problem"
    - "the infinite server problem"
    - "the h k server problem on bounded depth trees"
    - "facility location in evolving metrics"
    - "an algorithm for online k means clustering"
    - "dynamic facility location via exponential clocks"
    - "on the computation of fully proportional representation"

Connected through hyperedge HE-6 (induced by source paper "multistage vertex cover"):
  with members:
    - "multistage knapsack"
    - "temporal vertex cover with a sliding time window"
    - "temporal graph classes a view through temporal separators"
    - "fast dynamic graph algorithms for parameterized problems"
    - "the connectivity of boolean satisfiability computational and structural dichotomies"

Connected through hyperedge HE-7 (induced by source paper "multistage problems on a global budget"):
  with members:
    - "multistage vertex cover"
    - "online multistage subset maximization problems"
    - "multistage knapsack"
    - "facility location in evolving metrics"
    - "contracting graphs to paths and trees"

Connected through hyperedge HE-8 (induced by source paper "online multistage subset maximization problems"):
  with members:
    - "facility location in evolving metrics"
    - "dynamic facility location via exponential clocks"
    - "on the tradeoff between stability and fit"

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)