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: "approximately optimal mechanism design via differential privacy"
  Abstract: In this paper we study the implementation challenge in an abstract interdependent values model and an arbitrary objective function. We design a mechanism that allows for approximate optimal implementation of insensitive objective functions in ex-post Nash equilibrium. If, furthermore, values are private then the same mechanism is strategy proof. We cast our results onto two specific models: pricing and facility location. The mechanism we design is optimal up to an additive factor of the order of magnitude of one over the square root of the number of agents and involves no utility transfers. #R##N#Underlying our mechanism is a lottery between two auxiliary mechanisms: with high probability we actuate a mechanism that reduces players' influence on the choice of the social alternative, while choosing the optimal outcome with high probability. This is where the recent notion of differential privacy is employed. With the complementary probability we actuate a mechanism that is typically far from optimal but is incentive compatible. The joint mechanism inherits the desired properties from both.

Connected through hyperedge HE-1 (induced by source paper "facility location problem in differential privacy model revisited"):
  with members:
    - "scalable and jointly differentially private packing"
    - "near optimal jointly private packing algorithms via dual multiplicative weight update"
    - "on facility location with general lower bounds"
    - "private matchings and allocations"
    - "jointly private convex programming"
    - "calibrating data to sensitivity in private data analysis"
    - "mechanism design in large games incentives and privacy"
    - "differentially private combinatorial optimization"

Connected through hyperedge HE-2 (induced by source paper "social cost guarantees in smart route guidance"):
  with members:
    - "truthful facility assignment with resource augmentation an exact analysis of serial dictatorship"
    - "a compartmental model for traffic networks and its dynamical behavior"
    - "social welfare in one sided matchings random priority and beyond"
    - "a market inspired approach for intersection management in urban road traffic networks"

Connected through hyperedge HE-3 (induced by source paper "individual sensitivity preprocessing for data privacy"):
  with members:
    - "blender enabling local search with a hybrid differential privacy model"
    - "tight lower bounds for locally differentially private selection"
    - "the possibilities and limitations of private prediction markets"
    - "adaptive learning with robust generalization guarantees"
    - "efficient lipschitz extensions for high dimensional graph statistics and node private degree distributions"
    - "heterogeneous differential privacy"
    - "truthful linear regression"
    - "buying private data without verification"

Connected through hyperedge HE-4 (induced by source paper "learning optimal reserve price against non myopic bidders"):
  with members:
    - "multi scale online learning and its applications to online auctions"
    - "the price of differential privacy for online learning"
    - "learning simple auctions"
    - "jointly private convex programming"
    - "the sample complexity of revenue maximization"
    - "sampling and representation complexity of revenue maximization"
    - "making the most of your samples"
    - "perfect bayesian equilibria in repeated sales"

Connected through hyperedge HE-5 (induced by source paper "segmentation incentives and privacy"):
  with members:
    - "the strange case of privacy in equilibrium models"
    - "privacy and mechanism design"
    - "calibrating data to sensitivity in private data analysis"
    - "the exponential mechanism for social welfare private truthful and nearly optimal"
    - "privacy aware mechanism design"

Connected through hyperedge HE-6 (induced by source paper "jointly private convex programming"):
  with members:
    - "private matchings and allocations"
    - "privately solving linear programs"
    - "differentially private empirical risk minimization efficient algorithms and tight error bounds"
    - "privacy and truthful equilibrium selection for aggregative games"
    - "differential privacy for the analyst via private equilibrium computation"
    - "asymptotically truthful equilibrium selection in large congestion games"
    - "calibrating data to sensitivity in private data analysis"
    - "mechanism design in large games incentives and privacy"

Connected through hyperedge HE-7 (induced by source paper "the anarchy of scheduling without money"):
  with members:
    - "truthful assignment without money"

Connected through hyperedge HE-8 (induced by source paper "a game theoretic study on non monetary incentives in data analytics projects with privacy implications"):
  with members:
    - "budget feasible mechanisms for experimental design"
    - "what s the gist privacy preserving aggregation of user profiles"
    - "linear regression as a non cooperative game"
    - "crowd assisted search for price discrimination in e commerce first results"
    - "conducting truthful surveys cheaply"
    - "take it or leave it running a survey when privacy comes at a cost"
    - "truthful mechanisms for agents that value privacy"
    - "selling privacy at auction"

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.GT(Computer Science and Game Theory)