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: "the exponential mechanism for social welfare private truthful and nearly optimal"
  Abstract: In this paper we show that for any mechanism design problem with the objective of maximizing social welfare, the exponential mechanism can be implemented as a truthful mechanism while still preserving differential privacy. Our instantiation of the exponential mechanism can be interpreted as a generalization of the VCG mechanism in the sense that the VCG mechanism is the extreme case when the privacy parameter goes to infinity. To our knowledge, this is the first general tool for designing mechanisms that are both truthful and differentially private.

Connected through hyperedge HE-1 (induced by source paper "a differentially private incentive design for traffic offload to public transportation"):
  with members:
    - "model predictive control of autonomous mobility on demand systems"
    - "dynamic vehicle redistribution and online price incentives in shared mobility systems"

Connected through hyperedge HE-2 (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"
    - "privacy aware mechanism design"
    - "approximately optimal mechanism design via differential privacy"

Connected through hyperedge HE-3 (induced by source paper "bernoulli factories and black box reductions in mechanism design"):
  with members:
    - "near optimal online algorithms and fast approximation algorithms for resource allocation problems"
    - "non optimal mechanism design"
    - "fast algorithms for online stochastic convex programming"
    - "a near optimal dynamic learning algorithm for online matching problems with concave returns"
    - "bandits with knapsacks"
    - "multi parameter mechanisms with implicit payment computation"
    - "primal beats dual on online packing lps in the random order model"
    - "limitations of randomized mechanisms for combinatorial auctions"

Connected through hyperedge HE-4 (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-5 (induced by source paper "on the theory and practice of privacy preserving bayesian data analysis"):
  with members:
    - "on the differential privacy of bayesian inference"
    - "tuned models of peer assessment in moocs"
    - "calibrating data to sensitivity in private data analysis"
    - "on sampling anonymization and differential privacy or k anonymization meets differential privacy"

Connected through hyperedge HE-6 (induced by source paper "inferential privacy guarantees for differentially private mechanisms"):
  with members:
    - "calibrating data to sensitivity in private data analysis"
    - "on the semantics of differential privacy a bayesian formulation"

Connected through hyperedge HE-7 (induced by source paper "who to trust for truthfully maximizing welfare"):
  with members:
    - "truthful approximations to range voting"
    - "combinatorial auctions without money"
    - "on the power of deterministic mechanisms for facility location games"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"
    - "approximately optimal mechanism design via differential privacy"
    - "on the power of randomization in algorithmic mechanism design"
    - "optimal mechansim design and money burning"

Connected through hyperedge HE-8 (induced by source paper "robust mediators in large games"):
  with members:
    - "finding any nontrivial coarse correlated equilibrium is hard"
    - "privacy and truthful equilibrium selection for aggregative games"
    - "differential privacy for the analyst via private equilibrium computation"
    - "a learning theory approach to non interactive database privacy"
    - "iterative constructions and private data release"
    - "privately releasing conjunctions and the statistical query barrier"
    - "interactive privacy via the median mechanism"

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)