human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "an end to end argument in mechanism design prior independent auctions for budgeted agents"):
  Abstract: This paper considers prior-independent mechanism design, namely identifying a single mechanism that has near optimal performance on every prior distribution. We show that mechanisms with truthtelling equilibria, a.k.a., revelation mechanisms, do not always give optimal prior-independent mechanisms and we define the revelation gap to quantify the non-optimality of revelation mechanisms. This study suggests that it is important to develop a theory for the design of non-revelation mechanisms. #R##N#Our analysis focuses on single-item auctions for agents with budgets and the objectives of welfare and with a natural regularity assumption on the distribution. Our main results show that the all-pay auction (a non-revelation mechanism) is an optimal prior-independent approximation mechanism. The all-pay auction, however, is not a revelation mechanism. We prove that prior-independent approximation of best revelation mechanism is strictly worse than that of the all-pay auction. Thus, the revelation gap is at least a constant. Finally, we show that the clinching auction (a revelation mechanism) is a prior-independent $e\ \approx\ 2.714$ approximation. Thus the revelation gap is a constant. #R##N#Many of our analyses extend to the revenue objective, position environments, and irregular distributions.

Includes members:
  Member "a b testing of auctions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "estimating approximate incentive compatibility")
  Member "the price of anarchy in auctions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "complexity theory game theory and economics the barbados lectures")
  Member "randomization beats second price as a prior independent auction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "benchmark design and prior independent optimization")
  Member "approximate revenue maximization in interdependent value settings":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust revenue maximization under minimal statistical information")
  Member "mechanism design for data science":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "estimating approximate incentive compatibility")
  Member "simple and near optimal mechanisms for market intermediation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient two sided markets with limited information")
  Member "price of anarchy for auction revenue":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "simple credible and approximately optimal auctions")
  Member "efficiency guarantees in auctions with budgets":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a note on the efficiency of position mechanisms with budget constraints")

Question: Please tell me which class the source paper 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)