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 "mechanisms for risk averse agents without loss"):
  Abstract: Auctions in which agents' payoffs are random variables have received increased attention in recent years. In particular, recent work in algorithmic mechanism design has produced mechanisms employing internal randomization, partly in response to limitations on deterministic mechanisms imposed by computational complexity. For many of these mechanisms, which are often referred to as truthful-in-expectation, incentive compatibility is contingent on the assumption that agents are risk-neutral. These mechanisms have been criticized on the grounds that this assumption is too strong, because "real" agents are typically risk averse, and moreover their precise attitude towards risk is typically unknown a-priori. In response, researchers in algorithmic mechanism design have sought the design of universally-truthful mechanisms --- mechanisms for which incentive-compatibility makes no assumptions regarding agents' attitudes towards risk. #R##N#We show that any truthful-in-expectation mechanism can be generically transformed into a mechanism that is incentive compatible even when agents are risk averse, without modifying the mechanism's allocation rule. The transformed mechanism does not require reporting of agents' risk profiles. Equivalently, our result can be stated as follows: Every (randomized) allocation rule that is implementable in dominant strategies when players are risk neutral is also implementable when players are endowed with an arbitrary and unknown concave utility function for money.

Includes members:
  Member "a truthful randomized mechanism for combinatorial public projects via convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "probabilistic verification for obviously strategyproof mechanisms")
  Member "an approximately truthful in expectation mechanism for combinatorial auctions using value queries":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a truthful mechanism for the generalized assignment problem")
  Member "from convex optimization to randomized mechanisms toward optimal combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "robust mechanisms for risk averse sellers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mechanism design and risk aversion")
  Member "an impossibility result for truthful combinatorial auctions with submodular valuations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "truthfulness via proxies":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a bridge between liquid and social welfare in combinatorial auctions with submodular bidders")
  Member "on the power of randomization in algorithmic mechanism design":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the complexity of black box mechanism design with priors")

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)