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: "incentive compatible budget elicitation in multi unit auctions"
  Abstract: In this paper, we consider the problem of designing incentive compatible auctions for multiple (homogeneous) units of a good, when bidders have private valuations and private budget constraints. When only the valuations are private and the budgets are public, Dobzinski {\em et al} show that the {\em adaptive clinching} auction is the unique incentive-compatible auction achieving Pareto-optimality. They further show thatthere is no deterministic Pareto-optimal auction with private budgets. Our main contribution is to show the following Budget Monotonicity property of this auction: When there is only one infinitely divisible good, a bidder cannot improve her utility by reporting a budget smaller than the truth. This implies that a randomized modification to the adaptive clinching auction is incentive compatible and Pareto-optimal with private budgets. #R##N#The Budget Monotonicity property also implies other improved results in this context. For revenue maximization, the same auction improves the best-known competitive ratio due to Abrams by a factor of 4, and asymptotically approaches the performance of the optimal single-price auction. #R##N#Finally, we consider the problem of revenue maximization (or social welfare) in a Bayesian setting. We allow the bidders have public size constraints (on the amount of good they are willing to buy) in addition to private budget constraints. We show a simple poly-time computable 5.83-approximation to the optimal Bayesian incentive compatible mechanism, that is implementable in dominant strategies. Our technique again crucially needs the ability to prevent bidders from over-reporting budgets via randomization.

Connected through hyperedge HE-1 (induced by source paper "a simple mechanism for a budget constrained buyer"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "revenue maximization and ex post budget constraints"
    - "the menu size complexity of revenue approximation"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "mixture selection mechanism design and signaling"
    - "a simple and approximately optimal mechanism for an additive buyer"

Connected through hyperedge HE-2 (induced by source paper "polyhedral clinching auctions for two sided markets"):
  with members:
    - "clinching auctions beyond hard budget constraints"
    - "polyhedral clinching auctions and the adwords polytope"
    - "clinching auctions with online supply"

Connected through hyperedge HE-3 (induced by source paper "liquid price of anarchy"):
  with members:
    - "on the efficiency of the proportional allocation mechanism for divisible resources"
    - "mechanism design for crowdsourcing an optimal 1 1 e competitive budget feasible mechanism for large markets"
    - "improved efficiency guarantees in auctions with budgets"
    - "on the complexity of computing an equilibrium in combinatorial auctions"
    - "truthful multi unit procurements with budgets"
    - "price of anarchy for auction revenue"
    - "welfare guarantees for proportional allocations"
    - "combinatorial walrasian equilibrium"

Connected through hyperedge HE-4 (induced by source paper "truthful secretaries with budgets"):
  with members:
    - "polyhedral clinching auctions and the adwords polytope"
    - "clinching auctions with online supply"
    - "prior free auctions for budgeted agents"
    - "bayesian mechanism design for budget constrained agents"

Connected through hyperedge HE-5 (induced by source paper "a market for scheduling with applications to cloud computing"):
  with members:
    - "competitive algorithms from competitive equilibria non clairvoyant scheduling under polyhedral constraints"
    - "settling the complexity of arrow debreu equilibria in markets with additively separable utilities"
    - "online stochastic matching beating 1 1 e"

Connected through hyperedge HE-6 (induced by source paper "clinching auctions beyond hard budget constraints"):
  with members:
    - "efficiency guarantees in auctions with budgets"
    - "polyhedral clinching auctions and the adwords polytope"
    - "clinching auctions with online supply"
    - "prior free auctions for budgeted agents"
    - "bayesian mechanism design for budget constrained agents"
    - "general auction mechanism for search advertising"

Connected through hyperedge HE-7 (induced by source paper "monotonicity revenue equivalence and budgets"):
  with members:
    - "revenue maximization and ex post budget constraints"
    - "general auction mechanism for search advertising"

Connected through hyperedge HE-8 (induced by source paper "efficiency guarantees in auctions with budgets"):
  with members:
    - "polyhedral clinching auctions and the adwords polytope"
    - "clinching auctions with online supply"
    - "prior free auctions for budgeted agents"
    - "composable and efficient mechanisms"
    - "bayesian mechanism design for budget constrained agents"
    - "general auction mechanism for 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)