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: "randomized online algorithms for the buyback problem"
  Abstract: In the matroid buyback problem, an algorithm observes a sequence of bids and must decide whether to accept each bid at the moment it arrives, subject to a matroid constraint on the set of accepted bids. Decisions to reject bids are irrevocable, whereas decisions to accept bids may be canceled at a cost which is a fixed fraction of the bid value. We present a new randomized algorithm for this problem, and we prove matching upper and lower bounds to establish that the competitive ratio of this algorithm, against an oblivious adversary, is the best possible. We also observe that when the adversary is adaptive, no randomized algorithm can improve the competitive ratio of the optimal deterministic algorithm. Thus, our work completely resolves the question of what competitive ratios can be achieved by randomized algorithms for the matroid buyback problem.

Connected through hyperedge HE-1 (induced by source paper "online knapsack problems with a resource buffer"):
  with members:
    - "approximately stable matchings with general constraints"
    - "approximately stable matchings with budget constraints"
    - "near feasible stable matchings with budget constraints"

Connected through hyperedge HE-2 (induced by source paper "online submodular maximization with free disposal randomization beats 0 25 for partition matroids"):
  with members:
    - "streaming algorithms for submodular function maximization"
    - "online submodular maximization with preemption"
    - "deterministic algorithms for submodular maximization problems"
    - "submodular maximization meets streaming matchings matroids and more"
    - "on the hardness of welfare maximization in combinatorial auctions with submodular valuations"
    - "secretary problems with convex costs"

Connected through hyperedge HE-3 (induced by source paper "online submodular maximization with preemption"):
  with members:
    - "submodular maximization meets streaming matchings matroids and more"
    - "improved bounds for online preemptive matching"
    - "near optimal nonmyopic value of information in graphical models"
    - "symmetry and approximability of submodular maximization problems"
    - "buyback problem approximate matroid intersection with cancellation costs"
    - "constrained non monotone submodular maximization offline and secretary algorithms"
    - "oblivious algorithms for the maximum directed cut problem"
    - "submodular maximization by simulated annealing"

Connected through hyperedge HE-4 (induced by source paper "online bipartite matching with decomposable weights"):
  with members:
    - "matching with our eyes closed"
    - "improved bounds for online preemptive matching"
    - "buyback problem approximate matroid intersection with cancellation costs"
    - "online vertex weighted bipartite matching and single bid budgeted allocations"
    - "a dynamic near optimal algorithm for online linear programming"
    - "online stochastic matching beating 1 1 e"

Connected through hyperedge HE-5 (induced by source paper "buyback problem approximate matroid intersection with cancellation costs"):
  with members:
    - "improved approximation guarantees for weighted matching in the semi streaming model"
    - "algorithms for secretary problems on graphs and hypergraphs"

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.GT(Computer Science and Game Theory)