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: "correlation robust stochastic optimization"
  Abstract: We consider a robust model proposed by Scarf, 1958, for stochastic optimization when only the marginal probabilities of (binary) random variables are given, and the correlation between the random variables is unknown. In the robust model, the objective is to minimize expected cost against worst possible joint distribution with those marginals. We introduce the concept of correlation gap to compare this model to the stochastic optimization model that ignores correlations and minimizes expected cost under independent Bernoulli distribution. We identify a class of functions, using concepts of summable cost sharing schemes from game theory, for which the correlation gap is well-bounded and the robust model can be approximated closely by the independent distribution model. As a result, we derive efficient approximation factors for many popular cost functions, like submodular functions, facility location, and Steiner tree. As a byproduct, our analysis also yields some new results in the areas of social welfare maximization and existence of Walrasian equilibria, which may be of independent interest.

Connected through hyperedge HE-1 (induced by source paper "simple mechanisms for non linear agents"):
  with members:
    - "optimal auctions vs anonymous pricing beyond linear utility"
    - "optimal online contention resolution schemes via ex ante prophet inequalities"
    - "a simple mechanism for a budget constrained buyer"
    - "online contention resolution schemes"
    - "bayesian optimal auctions via multi to single agent reduction"
    - "the simple economics of approximately optimal auctions"
    - "mechanism design via correlation gap"

Connected through hyperedge HE-2 (induced by source paper "learning individually fair classifier with causal effect constraint"):
  with members:
    - "equality of opportunity in supervised learning"
    - "combinatorial prophet inequalities"
    - "a causal framework for discovering and removing direct and indirect discrimination"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-3 (induced by source paper "ranking an assortment of products via sequential submodular optimization"):
  with members:
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"
    - "submodular function maximization via the multilinear relaxation and contention resolution schemes"

Connected through hyperedge HE-4 (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 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"

Connected through hyperedge HE-5 (induced by source paper "distributionally robust submodular maximization"):
  with members:
    - "robust monotone submodular function maximization"
    - "robust optimization for non convex objectives"
    - "robust submodular maximization offline and online algorithms"
    - "stochastic submodular maximization the case of coverage functions"
    - "equilibrium computation and robust optimization in zero sum games with submodular structure"
    - "gradient methods for submodular maximization"
    - "robust budget allocation via continuous submodular functions"
    - "guaranteed non convex optimization submodular maximization over continuous domains"

Connected through hyperedge HE-6 (induced by source paper "equilibrium computation and robust optimization in zero sum games with submodular structure"):
  with members:
    - "robust optimization for non convex objectives"
    - "robust budget allocation via continuous submodular functions"
    - "algorithmic persuasion with no externalities"
    - "a reduction for optimizing lattice submodular functions with diminishing returns"
    - "the mysteries of security games equilibrium computation becomes combinatorial algorithm design"

Connected through hyperedge HE-7 (induced by source paper "algorithmic persuasion with no externalities"):
  with members:
    - "computational aspects of private bayesian persuasion"
    - "algorithmic bayesian persuasion"
    - "hardness results for signaling in bayesian zero sum and network routing games"
    - "mixture selection mechanism design and signaling"
    - "on the hardness of signaling"
    - "understanding incentives mechanism design becomes algorithm design"
    - "constrained signaling in auction design"
    - "send mixed signals earn more work less"

Connected through hyperedge HE-8 (induced by source paper "smoothness for simultaneous composition of mechanisms with admission"):
  with members:
    - "learning and efficiency in games with dynamic population"
    - "no regret learning in bayesian games"
    - "learning in auctions regret is hard envy is easy"
    - "on the complexity of computing an equilibrium in combinatorial auctions"
    - "jamming resistant learning in wireless networks"
    - "tight bounds for the price of anarchy of simultaneous first price auctions"
    - "bounding the inefficiency of outcomes in generalized second price auctions"
    - "composable and efficient mechanisms"

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)