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 "combinatorial prophet inequalities"):
  Abstract: We introduce a novel framework of Prophet Inequalities for combinatorial valuation functions. For a (non-monotone) submodular objective function over an arbitrary matroid feasibility constraint, we give an $O(1)$-competitive algorithm. For a monotone subadditive objective function over an arbitrary downward-closed feasibility constraint, we give an $O(\log n \log^2 r)$-competitive algorithm (where $r$ is the cardinality of the largest feasible subset). #R##N#Inspired by the proof of our subadditive prophet inequality, we also obtain an $O(\log n \cdot \log^2 r)$-competitive algorithm for the Secretary Problem with a monotone subadditive objective function subject to an arbitrary downward-closed feasibility constraint. Even for the special case of a cardinality feasibility constraint, our algorithm circumvents an $\Omega(\sqrt{n})$ lower bound by Bateni, Hajiaghayi, and Zadimoghaddam \cite{BHZ13-submodular-secretary_original} in a restricted query model. #R##N#En route to our submodular prophet inequality, we prove a technical result of independent interest: we show a variant of the Correlation Gap Lemma for non-monotone submodular functions.

Includes members:
  Member "beyond matroids secretary problem and prophet inequality with general constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "bayesian budget feasibility with posted pricing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "budget feasible mechanism design for non monotone submodular objectives offline and online")
  Member "secretary problems with non uniform arrival order":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "random order models")
  Member "streaming algorithms for submodular function maximization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "regularized submodular maximization at scale")
  Member "online submodular maximization with preemption":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "regularized submodular maximization at scale")
  Member "online contention resolution schemes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "building a good team secretary problems and the supermodular degree":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "beyond submodular maximization")
  Member "locally adaptive optimization adaptive seeding for monotone submodular functions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "efficient approximation algorithms for adaptive seed minimization")

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)