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 through blind strategies"
  Abstract: In the classic prophet inequality, samples from independent random variables arrive online. A gambler that knows the distributions must decide at each point in time whether to stop and pick the current sample or to continue and lose that sample forever. The goal of the gambler is to maximize the expected value of what she picks and the performance measure is the worst case ratio between the expected value the gambler gets and what a prophet, that sees all the realizations in advance, gets. In the late seventies, Krengel and Sucheston, and Gairing (1977) established that this worst case ratio is a universal constant equal to 1/2. In the last decade prophet inequalities has resurged as an important problem due to its connections to posted price mechanisms, frequently used in online sales. A very interesting variant is the Prophet Secretary problem, in which the only difference is that the samples arrive in a uniformly random order. For this variant several algorithms achieve a constant of 1-1/e and very recently this barrier was slightly improved. This paper analyzes strategies that set a nonincreasing sequence of thresholds to be applied at different times. The gambler stops the first time a sample surpasses the corresponding threshold. Specifically we consider a class of strategies called blind quantile strategies. They consist in fixing a function which is used to define a sequence of thresholds once the instance is revealed. Our main result shows that they can achieve a constant of 0.665, improving upon the best known result of Azar et al. (2018), and on Beyhaghi et al. (2018) (order selection). Our proof analyzes precisely the underlying stopping time distribution, relying on Schur-convexity theory. We further prove that blind strategies cannot achieve better than 0.675. Finally we prove that no nonadaptive algorithm for the gambler can achieve better than 0.732.

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"
    - "stochastic bandits robust to adversarial corruptions"
    - "optimal online contention resolution schemes via ex ante prophet inequalities"
    - "prophet secretary surpassing the 1 1 e barrier"
    - "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 surpassing the 1 1 e barrier"
    - "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"
    - "nearly optimal pricing algorithms for production constrained and laminar bayesian selection"
    - "random order contention resolution schemes"
    - "prophet secretary surpassing the 1 1 e barrier"
    - "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 "assortment auctions a myersonian characterization for markov chain based choice models"):
  with members:
    - "prophet inequalities on the intersection of a matroid and a graph"
    - "multi stage and multi customer assortment optimization with inventory constraints"
    - "a duality based unified approach to bayesian mechanism design"
    - "dynamic pricing under a static calendar"
    - "improved approximations for free order prophets and second price auctions"
    - "on policies for single leg revenue management with limited demand information"
    - "welfare maximization and truthfulness in mechanism design with ordinal preferences"
    - "mechanism design via correlation gap"

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 surpassing the 1 1 e barrier"
    - "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 surpassing the 1 1 e barrier"
    - "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:
    - "improved approximations for free order prophets and second price auctions"
    - "prophet secretary surpassing the 1 1 e barrier"
    - "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 "tight revenue gaps among simple mechanisms"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "nearly optimal pricing algorithms for production constrained and laminar bayesian selection"
    - "improved approximations for free order prophets and second price auctions"
    - "tight approximation ratio of anonymous pricing"
    - "approximate revenue maximization with multiple items"
    - "prophet secretary surpassing the 1 1 e barrier"
    - "prophet secretary for combinatorial auctions and matroids"
    - "simple mechanisms for subadditive buyers via duality"

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)