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: "on the power of randomization in algorithmic mechanism design"
  Abstract: In many settings the power of truthful mechanisms is severely bounded. In this paper we use randomization to overcome this problem. In particular, we construct an FPTAS for multi-unit auctions that is truthful in expectation, whereas there is evidence that no polynomial-time truthful deterministic mechanism provides an approximation ratio better than 2. #R##N#We also show for the first time that truthful in expectation polynomial-time mechanisms are \emph{provably} stronger than polynomial-time universally truthful mechanisms. Specifically, we show that there is a setting in which: (1) there is a non-polynomial time truthful mechanism that always outputs the optimal solution, and that (2) no universally truthful randomized mechanism can provide an approximation ratio better than 2 in polynomial time, but (3) an FPTAS that is truthful in expectation exists.

Connected through hyperedge HE-1 (induced by source paper "the complexity of black box mechanism design with priors"):
  with members:
    - "on black box transformations in downward closed environments"
    - "bernoulli factories and black box reductions in mechanism design"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "non optimal mechanism design"
    - "reducing revenue to welfare maximization approximation algorithms and other generalizations"
    - "optimal multi dimensional mechanism design reducing revenue to welfare maximization"
    - "bayesian incentive compatibility via fractional assignments"

Connected through hyperedge HE-2 (induced by source paper "new mechanism for repeated posted price auction with a strategic buyer without discounting"):
  with members:
    - "on consistency of optimal pricing algorithms in repeated posted price auctions with strategic buyer"
    - "perfect bayesian equilibria in repeated sales"
    - "learning prices for repeated auctions with strategic buyers"

Connected through hyperedge HE-3 (induced by source paper "interdependent values without single crossing"):
  with members:
    - "approximate revenue maximization in interdependent value settings"

Connected through hyperedge HE-4 (induced by source paper "a general theory of sample complexity for multi item profit maximization"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "submultiplicative glivenko cantelli and uniform convergence of revenues"
    - "learning multi item auctions with or without samples"
    - "revenue optimization with approximate bid predictions"
    - "a sample complexity measure with applications to learning optimal auctions"
    - "learning simple auctions"
    - "do prices coordinate markets"

Connected through hyperedge HE-5 (induced by source paper "data centric mobile crowdsensing"):
  with members:
    - "scalable mobile crowdsensing via peer to peer data sharing"
    - "two sided matching based cooperative spectrum sharing"
    - "economic analysis of crowdsourced wireless community networks"
    - "centurion incentivizing multi requester mobile crowd sensing"
    - "dynamic routing for social information sharing"
    - "providing long term participation incentive in participatory sensing"
    - "distributed time sensitive task selection in mobile crowdsensing"
    - "combining spot and futures markets a hybrid market approach to dynamic spectrum access"

Connected through hyperedge HE-6 (induced by source paper "computational efficiency requires simple taxation"):
  with members:
    - "breaking the logarithmic barrier for truthful combinatorial auctions with submodular bidders"
    - "inapproximability of truthful mechanisms via generalizations of the vc dimension"
    - "economic efficiency requires interaction"
    - "multi parameter mechanisms with implicit payment computation"
    - "the menu size complexity of auctions"
    - "the computational complexity of truthfulness in combinatorial auctions"
    - "from convex optimization to randomized mechanisms toward optimal combinatorial auctions"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"

Connected through hyperedge HE-7 (induced by source paper "a note on relaxation and rounding in algorithmic mechanism design"):
  with members:
    - "generalized assignment problem truthful mechanism design without money"
    - "a truthful in expectation mechanism for the generalized assignment problem"
    - "from convex optimization to randomized mechanisms toward optimal combinatorial auctions"
    - "truthful assignment without money"
    - "truthfulness via proxies"

Connected through hyperedge HE-8 (induced by source paper "truthfulness with value maximizing bidders"):
  with members:
    - "bundling equilibrium in combinatorial auctions"

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)