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: "bayesian mechanism design for budget constrained agents"
  Abstract: We study Bayesian mechanism design problems in settings where agents have budgets. Specifically, an agent's utility for an outcome is given by his value for the outcome minus any payment he makes to the mechanism, as long as the payment is below his budget, and is negative infinity otherwise. This discontinuity in the utility function presents a significant challenge in the design of good mechanisms, and classical "unconstrained" mechanisms fail to work in settings with budgets. The goal of this paper is to develop general reductions from budget-constrained Bayesian MD to unconstrained Bayesian MD with small loss in performance. We consider this question in the context of the two most well-studied objectives in mechanism design---social welfare and revenue---and present constant factor approximations in a number of settings. Some of our results extend to settings where budgets are private and agents need to be incentivized to reveal them truthfully.

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 "an end to end argument in mechanism design prior independent auctions for budgeted agents"):
  with members:
    - "a b testing of auctions"
    - "the price of anarchy in auctions"
    - "randomization beats second price as a prior independent auction"
    - "approximate revenue maximization in interdependent value settings"
    - "mechanism design for data science"
    - "simple and near optimal mechanisms for market intermediation"
    - "price of anarchy for auction revenue"
    - "efficiency guarantees in auctions with budgets"

Connected through hyperedge HE-3 (induced by source paper "the menu complexity of one and a half dimensional mechanism design"):
  with members:
    - "approximate revenue maximization with multiple items"
    - "learning simple auctions"
    - "the menu size complexity of revenue approximation"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "the sample complexity of revenue maximization"
    - "the sample complexity of auctions with side information"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "a simple and approximately optimal mechanism for an additive buyer"

Connected through hyperedge HE-4 (induced by source paper "revenue maximization and ex post budget constraints"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "an n to 1 bidder reduction for multi item auctions and its applications"
    - "revenue maximization for selling multiple correlated items"
    - "bayesian truthful mechanisms for job scheduling from bi criterion approximation algorithms"
    - "understanding incentives mechanism design becomes algorithm design"

Connected through hyperedge HE-5 (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-6 (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"
    - "incentive compatible budget elicitation in multi unit auctions"

Connected through hyperedge HE-7 (induced by source paper "applications of alpha strongly regular distributions to bayesian auctions"):
  with members:
    - "the sample complexity of revenue maximization"
    - "on the ratio of revenue to welfare in single parameter mechanism design"
    - "budget constrained auctions with heterogeneous items"

Connected through hyperedge HE-8 (induced by source paper "improved efficiency guarantees in auctions with budgets"):
  with members:
    - "efficiency guarantees in auctions with budgets"
    - "budget feasible mechanism design from prior free to bayesian"
    - "prior free auctions for budgeted agents"
    - "composable and efficient mechanisms"
    - "competitive auctions for markets with positive externalities"
    - "on the approximability of budget feasible mechanisms"
    - "budget feasible mechanisms"

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)