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 submodular secretary problem goes linear"):
  Abstract: During the last decade, the matroid secretary problem (MSP) became one of the most prominent classes of online selection problems. Partially linked to its numerous applications in mechanism design, substantial interest arose also in the study of nonlinear versions of MSP, with a focus on the submodular matroid secretary problem (SMSP). So far, O(1)-competitive algorithms have been obtained for SMSP over some basic matroid classes. This created some hope that, analogously to the matroid secretary conjecture, one may even obtain O(1)-competitive algorithms for SMSP over any matroid. However, up to now, most questions related to SMSP remained open, including whether SMSP may be substantially more difficult than MSP; and more generally, to what extend MSP and SMSP are related. #R##N#Our goal is to address these points by presenting general black-box reductions from SMSP to MSP. In particular, we show that any O(1)-competitive algorithm for MSP, even restricted to a particular matroid class, can be transformed in a black-box way to an O(1)-competitive algorithm for SMSP over the same matroid class. This implies that the matroid secretary conjecture is equivalent to the same conjecture for SMSP. Hence, in this sense SMSP is not harder than MSP. Also, to find O(1)-competitive algorithms for SMSP over a particular matroid class, it suffices to consider MSP over the same matroid class. Using our reductions we obtain many first and improved O(1)-competitive algorithms for SMSP over various matroid classes by leveraging known algorithms for MSP. Moreover, our reductions imply an O(loglog(rank))-competitive algorithm for SMSP, thus, matching the currently best asymptotic algorithm for MSP, and substantially improving on the previously best O(log(rank))-competitive algorithm for SMSP.

Includes members:
  Member "o log log rank competitive ratio for the matroid secretary problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "submodular matroid secretary problem with shortlists")
  Member "a simple o log log mathrm rank competitive algorithm for the matroid secretary problem":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "submodular matroid secretary problem with shortlists")
  Member "prophet inequalities with limited information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "advances on matroid secretary problems free order model and laminar case":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "strong algorithms for the ordinal matroid secretary problem")
  Member "matroid secretary for regular and decomposable matroids":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "strong algorithms for the ordinal matroid secretary problem")
  Member "secretary problems with convex costs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "online learning for min max discrete problems")
  Member "the simulated greedy algorithm for several submodular matroid secretary problems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an improved algorithm for the submodular secretary problem with a cardinality constraint")
  Member "submodular function maximization via the multilinear relaxation and contention resolution schemes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "approximability of monotone submodular function maximization under cardinality and matroid constraints in the streaming model")

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)