human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "liquid price of anarchy"):
  Abstract: Incorporating budget constraints into the analysis of auctions has become increasingly important, as they model practical settings more accurately. The social welfare function, which is the standard measure of efficiency in auctions, is inadequate for settings with budgets, since there may be a large disconnect between the value a bidder derives from obtaining an item and what can be liquidated from her. The Liquid Welfare objective function has been suggested as a natural alternative for settings with budgets. Simple auctions, like simultaneous item auctions, are evaluated by their performance at equilibrium using the Price of Anarchy (PoA) measure -- the ratio of the objective function value of the optimal outcome to the worst equilibrium. Accordingly, we evaluate the performance of simultaneous item auctions in budgeted settings by the Liquid Price of Anarchy (LPoA) measure -- the ratio of the optimal Liquid Welfare to the Liquid Welfare obtained in the worst equilibrium. #R##N#Our main result is that the LPoA for mixed Nash equilibria is bounded by a constant when bidders are additive and items can be divided into sufficiently many discrete parts. Our proofs are robust, and can be extended to achieve similar bounds for simultaneous second price auctions as well as Bayesian Nash equilibria. For pure Nash equilibria, we establish tight bounds on the LPoA for the larger class of fractionally-subadditive valuations. To derive our results, we develop a new technique in which some bidders deviate (surprisingly) toward a non-optimal solution. In particular, this technique does not fit into the smoothness framework.

Includes members:
  Member "on the efficiency of the proportional allocation mechanism for divisible resources":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a note on the efficiency of position mechanisms with budget constraints")
  Member "mechanism design for crowdsourcing an optimal 1 1 e competitive budget feasible mechanism for large markets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "budget feasible mechanism design for non monotone submodular objectives offline and online")
  Member "improved efficiency guarantees in auctions with budgets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a note on the efficiency of position mechanisms with budget constraints")
  Member "on the complexity of computing an equilibrium in combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on simultaneous two player combinatorial auctions")
  Member "truthful multi unit procurements with budgets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "approximately maximizing the broker s profit in a two sided market")
  Member "price of anarchy for auction revenue":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "simple credible and approximately optimal auctions")
  Member "welfare guarantees for proportional allocations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a note on the efficiency of position mechanisms with budget constraints")
  Member "combinatorial walrasian equilibrium":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the power and limits of dynamic pricing in combinatorial markets")

Question: Please tell me which class the source paper 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)