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 "truthful mechanisms with implicit payment computation"):
  Abstract: It is widely believed that computing payments needed to induce truthful bidding is somehow harder than simply computing the allocation. We show that the opposite is true: creating a randomized truthful mechanism is essentially as easy as a single call to a monotone allocation rule. Our main result is a general procedure to take a monotone allocation rule for a single-parameter domain and transform it (via a black-box reduction) into a randomized mechanism that is truthful in expectation and individually rational for every realization. The mechanism implements the same outcome as the original allocation rule with probability arbitrarily close to 1, and requires evaluating that allocation rule only once. We also provide an extension of this result to multi-parameter domains and cycle-monotone allocation rules, under mild star-convexity and non-negativity hypotheses on the type space and allocation rule, respectively. #R##N#Because our reduction is simple, versatile, and general, it has many applications to mechanism design problems in which re-evaluating the allocation rule is either burdensome or informationally impossible. Applying our result to the multi-armed bandit problem, we obtain truthful randomized mechanisms whose regret matches the information-theoretic lower bound up to logarithmic factors, even though prior work showed this is impossible for truthful deterministic mechanisms. We also present applications to offline mechanism design, showing that randomization can circumvent a communication complexity lower bound for deterministic payments computation, and that it can also be used to create truthful shortest path auctions that approximate the welfare of the VCG allocation arbitrarily well, while having the same running time complexity as Dijkstra's algorithm.

Includes members:
  Member "bayesian truthful mechanisms for job scheduling from bi criterion approximation algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "persuasion and incentives through the lens of duality")
  Member "truthful prioritization schemes for spectrum sharing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi parameter mechanisms with implicit payment computation")
  Member "reducing revenue to welfare maximization approximation algorithms and other generalizations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal mechanisms for selling two items to a single buyer having uniformly distributed valuations")
  Member "understanding incentives mechanism design becomes algorithm design":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of contracts")
  Member "multi parameter mechanisms with implicit payment computation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an efficient e bic to bic transformation and its application to black box reduction in revenue maximization")
  Member "optimal multi dimensional mechanism design reducing revenue to welfare maximization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "the exponential mechanism for social welfare private truthful and nearly optimal":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a differentially private incentive design for traffic offload to public transportation")
  Member "single call mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "computational efficiency requires simple taxation")

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)