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 "combinatorial walrasian equilibrium"):
  Abstract: We study a combinatorial market design problem, where a collection of indivisible objects is to be priced and sold to potential buyers subject to equilibrium constraints.The classic solution concept for such problems is Walrasian Equilibrium (WE), which provides a simple and transparent pricing structure that achieves optimal social welfare. The main weakness of the WE notion is that it exists only in very restrictive cases. To overcome this limitation, we introduce the notion of a Combinatorial Walrasian equilibium (CWE), a natural relaxation of WE. The difference between a CWE and a (non-combinatorial) WE is that the seller can package the items into indivisible bundles prior to sale, and the market does not necessarily clear. #R##N#We show that every valuation profile admits a CWE that obtains at least half of the optimal (unconstrained) social welfare. Moreover, we devise a poly-time algorithm that, given an arbitrary allocation X, computes a CWE that achieves at least half of the welfare of X. Thus, the economic problem of finding a CWE with high social welfare reduces to the algorithmic problem of social-welfare approximation. In addition, we show that every valuation profile admits a CWE that extracts a logarithmic fraction of the optimal welfare as revenue. Finally, these results are complemented by strong lower bounds when the seller is restricted to using item prices only, which motivates the use of bundles. The strength of our results derives partly from their generality - our results hold for arbitrary valuations that may exhibit complex combinations of substitutes and complements.

Includes members:
  Member "clearing markets via bundles":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the power and limits of dynamic pricing in combinatorial markets")
  Member "welfare and revenue guarantees for competitive bundling equilibrium":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a general framework for endowment effects in combinatorial markets")
  Member "combinatorial auctions via posted prices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "understanding incentives mechanism design becomes algorithm design":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of contracts")
  Member "lower bound for envy free and truthful makespan approximation on related machines":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "envy regret and social welfare loss")
  Member "optimization with demand oracles":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "tight approximation for unconstrained xos maximization")
  Member "an impossibility result for truthful combinatorial auctions with submodular valuations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "bayesian incentive compatibility via fractional assignments":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an efficient e bic to bic transformation and its application to black box reduction in revenue maximization")

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)