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: "efficiency revenue trade offs in auctions"
  Abstract: When agents with independent priors bid for a single item, Myerson's optimal auction maximizes expected revenue, whereas Vickrey's second-price auction optimizes social welfare. We address the natural question of trade-offs between the two criteria, that is, auctions that optimize, say, revenue under the constraint that the welfare is above a given level. If one allows for randomized mechanisms, it is easy to see that there are polynomial-time mechanisms that achieve any point in the trade-off (the Pareto curve) between revenue and welfare. We investigate whether one can achieve the same guarantees using deterministic mechanisms. We provide a negative answer to this question by showing that this is a (weakly) NP-hard problem. On the positive side, we provide polynomial-time deterministic mechanisms that approximate with arbitrary precision any point of the trade-off between these two fundamental objectives for the case of two bidders, even when the valuations are correlated arbitrarily. The major problem left open by our work is whether there is such an algorithm for three or more bidders with independent valuation distributions.

Connected through hyperedge HE-1 (induced by source paper "price doubling and item halving robust revenue guarantees for item pricing"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "simple mechanisms for subadditive buyers via duality"
    - "envy free pricing in multi unit markets"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "pricing to maximize revenue and welfare simultaneously in large markets"
    - "on the computational complexity of optimal simple mechanisms"
    - "on welfare approximation and stable pricing"
    - "secretary problems with non uniform arrival order"

Connected through hyperedge HE-2 (induced by source paper "pricing to maximize revenue and welfare simultaneously in large markets"):
  with members:
    - "do prices coordinate markets"
    - "the sample complexity of revenue maximization"
    - "envy free pricing in large markets approximating revenue and welfare"
    - "applications of alpha strongly regular distributions to bayesian auctions"
    - "optimising trade offs among stakeholders in ad auctions"
    - "on the ratio of revenue to welfare in single parameter mechanism design"
    - "pricing ad slots with consecutive multi unit demand"
    - "lower bounds on revenue of approximately optimal auctions"

Connected through hyperedge HE-3 (induced by source paper "optimising trade offs among stakeholders in ad auctions"):
  with members:
    - "ranking and tradeoffs in sponsored search auctions"
    - "refine predictions ad infinitum"

Connected through hyperedge HE-4 (induced by source paper "general truthfulness characterizations via convex analysis"):
  with members:
    - "the lovasz bregman divergence and connections to rank aggregation clustering and web ranking"
    - "designing markets for daily deals"
    - "approaching utopia strong truthfulness and externality resistant mechanisms"
    - "eliciting forecasts from self interested experts scoring rules for decision makers"
    - "a new understanding of prediction markets via no regret learning"
    - "statistical exponential families a digest with flash cards"
    - "characterizing truthful multi armed bandit mechanisms"
    - "algorithmic methods for sponsored search advertising"

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)