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: "optimising trade offs among stakeholders in ad auctions"
  Abstract: We examine trade-offs among stakeholders in ad auctions. Our metrics are the revenue for the utility of the auctioneer, the number of clicks for the utility of the users and the welfare for the utility of the advertisers. We show how to optimize linear combinations of the stakeholder utilities, showing that these can be tackled through a GSP auction with a per-click reserve price. We then examine constrained optimization of stakeholder utilities. #R##N#We use simulations and analysis of real-world sponsored search auction data to demonstrate the feasible trade-offs, examining the effect of changing the allowed number of ads on the utilities of the stakeholders. We investigate both short term effects, when the players do not have the time to modify their behavior, and long term equilibrium conditions. #R##N#Finally, we examine a combinatorially richer constrained optimization problem, where there are several possible allowed configurations (templates) of ad formats. This model captures richer ad formats, which allow using the available screen real estate in various ways. We show that two natural generalizations of the GSP auction rules to this domain are poorly behaved, resulting in not having a symmetric Nash equilibrium or having one with poor welfare. We also provide positive results for restricted cases.

Connected through hyperedge HE-1 (induced by source paper "a price per attention auction scheme using mouse cursor information"):
  with members:
    - "attention is all you need"
    - "ranking and tradeoffs in sponsored search auctions"
    - "doubleclick ad exchange auction"

Connected through hyperedge HE-2 (induced by source paper "aiads automated and intelligent advertising system for sponsored search"):
  with members:
    - "deep reinforcement learning for sponsored search real time bidding"
    - "beyond keywords and relevance a personalized ad retrieval framework in e commerce sponsored search"
    - "roi constrained auctions"
    - "optimized cost per click in taobao display advertising"
    - "sponsored search auctions with rich ads"
    - "mechanism design for value maximizers"
    - "scalable semantic matching of queries to ads in sponsored search advertising"
    - "fast core pricing for rich advertising auctions"

Connected through hyperedge HE-3 (induced by source paper "learning adaptive display exposure for real time advertising"):
  with members:
    - "deep reinforcement learning for sponsored search real time bidding"
    - "reward constrained policy optimization"
    - "reinforcement learning to rank in e commerce search engine formalization analysis and application"
    - "budget constrained bidding by model free reinforcement learning in display advertising"
    - "hindsight experience replay"
    - "reinforcement mechanism design for e commerce"
    - "real time bidding by reinforcement learning in display advertising"
    - "constrained policy optimization"

Connected through hyperedge HE-4 (induced by source paper "optimizing trade offs among stakeholders in real time bidding by incorporating multimedia metrics"):
  with members:
    - "risk aware dynamic reserve prices of programmatic guarantee in display advertising"
    - "a dynamic pricing model for unifying programmatic guarantee and real time bidding in display advertising"
    - "a lattice framework for pricing display advertisement options with the stochastic volatility underlying model"
    - "ranking and tradeoffs in sponsored search auctions"
    - "multi keyword multi click advertisement option contracts for sponsored search"

Connected through hyperedge HE-5 (induced by source paper "gsp the cinderella of mechanism design"):
  with members:
    - "sponsored search auctions with rich ads"
    - "truthful outcomes from non truthful position auctions"
    - "gsp with general independent click through rates"
    - "position auctions with externalities and brand effects"
    - "general auction mechanism for search advertising"

Connected through hyperedge HE-6 (induced by source paper "sponsored search auctions with rich ads"):
  with members:
    - "gsp the cinderella of mechanism design"
    - "mechanism design for value maximizers"
    - "truthful outcomes from non truthful position auctions"
    - "gsp with general independent click through rates"
    - "a dynamic axiomatic approach to first price auctions"

Connected through hyperedge HE-7 (induced by source paper "towards global optimization in display advertising by integrating multimedia metrics with real time bidding"):
  with members:
    - "optimizing trade offs among stakeholders in real time bidding by incorporating multimedia metrics"
    - "ad exchange envy free auctions with mediators"

Connected through hyperedge HE-8 (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"
    - "on the ratio of revenue to welfare in single parameter mechanism design"
    - "pricing ad slots with consecutive multi unit demand"
    - "efficiency revenue trade offs in auctions"
    - "lower bounds on revenue of approximately optimal 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)