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 "the bayesian prophet a low regret framework for online decision making"):
  Abstract: Motivated by the success of using black-box predictive algorithms as subroutines for online decision-making, we develop a new framework for designing online policies given access to an oracle providing statistical information about an offline benchmark. Having access to such prediction oracles enables simple and natural Bayesian selection policies, and raises the question as to how these policies perform in different settings. Our work makes two important contributions towards tackling this question: First, we develop a general technique we call *compensated coupling* which can be used to derive bounds on the expected regret (i.e., additive loss with respect to a benchmark) for any online policy and offline benchmark; Second, using this technique, we show that the Bayes Selector has constant expected regret (i.e., independent of the number of arrivals and resource levels) in any online packing and matching problem with a finite type-space. Our results generalize and simplify many existing results for online packing and matching problems, and suggest a promising pathway for obtaining oracle-driven policies for other online decision-making settings.

Includes members:
  Member "near optimal online algorithms and fast approximation algorithms for resource allocation problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "online stochastic max weight matching prophet inequality for vertex and edge arrival models")
  Member "online stochastic matching new algorithms and bounds":
    also connected through other hyperedges:
      (none)
  Member "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the power and limits of dynamic pricing in combinatorial markets")
  Member "new algorithms better bounds and a novel model for online stochastic matching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online graph matching problems with a worst case reassignment budget")
  Member "online convex optimization using predictions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "beyond no regret competitive control via online optimization with memory")
  Member "algorithms with logarithmic or sublinear regret for constrained contextual bandits":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "achieving fairness in the stochastic multi armed bandit problem")
  Member "fast algorithms for online stochastic convex programming":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "simple and fast algorithm for binary integer and online linear programming")
  Member "bandits with knapsacks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exploration exploitation in constrained mdps")

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)