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: "note on vcg vs price raising for matching markets"
  Abstract: In [1] the use of VCG in matching markets is motivated by saying that in order to compute market clearing prices in a matching market, the auctioneer needs to know the true valuations of the bidders. Hence VCG and corresponding personalized prices are proposed as an incentive compatible mechanism. The same line of argument pops up in several lecture sheets and other documents related to courses based on Easley and Kleinberg’s book, seeming to suggest that computing market clearing prices and corresponding assignments were not incentive compatible. Main purpose of our note is to observe that, in contrast, assignments based on buyer optimal market clearing prices are indeed incentive compatible. keywords: matching markets, market clearing prices, VCG mechanism.

Connected through hyperedge HE-1 (induced by source paper "envy regret and social welfare loss"):
  with members:
    - "the ad types problem"
    - "online learning for measuring incentive compatibility in ad auctions"
    - "communication complexity of approximate nash equilibria"
    - "the price of anarchy in auctions"
    - "setting lower bounds on truthfulness"
    - "learning in auctions regret is hard envy is easy"
    - "adam a method for stochastic optimization"
    - "gsp with general independent click through rates"

Connected through hyperedge HE-2 (induced by source paper "the ad types problem"):
  with members:
    - "sponsored search auctions with rich ads"
    - "fast core pricing for rich advertising auctions"
    - "ad auctions and cascade model gsp inefficiency and algorithms"
    - "ironing in the dark"
    - "sponsored search market equilibria and the hungarian method"
    - "sponsored search auctions with markovian users"

Connected through hyperedge HE-3 (induced by source paper "descending price algorithm for determining market clearing prices in matching markets"):
  with members:
    - "a dynamic axiomatic approach to first price auctions"
    - "optimal multi dimensional mechanism design reducing revenue to welfare maximization"
    - "the complexity of optimal mechanism design"

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)