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: "prophet secretary surpassing the 1 1 e barrier"
  Abstract: In the Prophet Secretary problem, samples from a known set of probability distributions arrive one by one in a uniformly random order, and an algorithm must irrevocably pick one of the samples as soon as it arrives. The goal is to maximize the expected value of the sample picked relative to the expected maximum of the distributions. This is one of the most simple and fundamental problems in online decision making that models the process selling one item to a sequence of costumers. For a closely related problem called the Prophet Inequality where the order of the random variables is adversarial, it is known that one can achieve in expectation $1/2$ of the expected maximum, and no better ratio is possible. For the Prophet Secretary problem, that is, when the variables arrive in a random order, Esfandiari et al.\ (ESA 2015) showed that one can actually get $1-1/e$ of the maximum. The $1-1/e$ bound was recently extended to more general settings (Ehsani et al., 2017). Given these results, one might be tempted to believe that $1-1/e$ is the correct bound. We show that this is not the case by providing an algorithm for the Prophet Secretary problem that beats the $1-1/e$ bound and achieves $1-1/e+1/400$ of the optimum value. We also prove a hardness result on the performance of algorithms under a natural restriction which we call deterministic distribution-insensitivity.

Connected through hyperedge HE-1 (induced by source paper "prophet inequalities with linear correlations and augmentations"):
  with members:
    - "optimal single choice prophet inequalities from samples"
    - "robust algorithms for the secretary problem"
    - "prophet secretary through blind strategies"
    - "stochastic bandits robust to adversarial corruptions"
    - "optimal online contention resolution schemes via ex ante prophet inequalities"
    - "robustly learning a gaussian getting optimal error efficiently"
    - "prophet secretary for combinatorial auctions and matroids"
    - "online allocation with traffic spikes mixing adversarial and stochastic models"

Connected through hyperedge HE-2 (induced by source paper "predict and match prophet inequalities with uncertain supply"):
  with members:
    - "prophet secretary through blind strategies"
    - "prophet secretary for combinatorial auctions and matroids"
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"
    - "combinatorial prophet inequalities"
    - "combinatorial auctions via posted prices"
    - "matroid prophet inequalities"
    - "bayesian combinatorial auctions expanding single buyer mechanisms to many buyers"
    - "approximation algorithms for correlated knapsacks and non martingale bandits"

Connected through hyperedge HE-3 (induced by source paper "optimal single choice prophet inequalities from samples"):
  with members:
    - "prophet inequality for bipartite matching merits of being simple and non adaptive"
    - "prophet secretary through blind strategies"
    - "nearly optimal pricing algorithms for production constrained and laminar bayesian selection"
    - "random order contention resolution schemes"
    - "pricing for online resource allocation intervals and paths"
    - "prophet secretary for combinatorial auctions and matroids"
    - "combinatorial prophet inequalities"
    - "beyond matroids secretary problem and prophet inequality with general constraints"

Connected through hyperedge HE-4 (induced by source paper "the outer limits of contention resolution on matroids and connections to the secretary problem"):
  with members:
    - "the prophet inequality can be solved optimally with a single set of samples"
    - "random order contention resolution schemes"
    - "optimal online contention resolution schemes via ex ante prophet inequalities"
    - "prophet secretary for combinatorial auctions and matroids"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "online contention resolution schemes"
    - "o log log rank competitive ratio for the matroid secretary problem"
    - "a simple o log log mathrm rank competitive algorithm for the matroid secretary problem"

Connected through hyperedge HE-5 (induced by source paper "improved approximations for posted price mechanisms second price auctions and free order prophets"):
  with members:
    - "prophet secretary through blind strategies"
    - "prophet secretary for combinatorial auctions and matroids"
    - "a field guide to personalized reserve prices"
    - "combinatorial auctions via posted prices"
    - "mechanism design via correlation gap"
    - "the power of randomness in bayesian optimal mechanism design"
    - "approximation schemes for sequential posted pricing in multi unit auctions"
    - "correlation robust stochastic optimization"

Connected through hyperedge HE-6 (induced by source paper "on optimal ordering in the optimal stopping problem"):
  with members:
    - "prophet secretary through blind strategies"
    - "prophet secretary for combinatorial auctions and matroids"
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"
    - "combinatorial prophet inequalities"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "a simple o log log mathrm rank competitive algorithm for the matroid secretary problem"
    - "matroid prophet inequalities"
    - "bayesian combinatorial auctions expanding single buyer mechanisms to many buyers"

Connected through hyperedge HE-7 (induced by source paper "lp based approximation for personalized reserve prices"):
  with members:
    - "prophet secretary through blind strategies"
    - "improved approximations for free order prophets and second price auctions"
    - "a field guide to personalized reserve prices"
    - "making the most of your samples"
    - "learning theory and algorithms for revenue optimization in second price auctions with reserve"
    - "mechanism design via correlation gap"
    - "optimal auctions with correlated bidders are easy"

Connected through hyperedge HE-8 (induced by source paper "how to hire secretaries with stochastic departures"):
  with members:
    - "online trading as a secretary problem"
    - "packing returning secretaries"
    - "improved approximations for free order prophets and second price auctions"
    - "prophet secretary for combinatorial auctions and matroids"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "o log log rank competitive ratio for the matroid secretary problem"
    - "matroid prophet inequalities"

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)