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 "approximately efficient two sided combinatorial auctions"):
  Abstract: Mechanism design for one-sided markets has been investigated for several decades in economics and in computer science. More recently, there has been an increased attention on mechanisms for two-sided markets, in which buyers and sellers act strategically. For two-sided markets, an impossibility result of Myerson and Satterthwaite states that no mechanism can simultaneously satisfy individual rationality (IR), incentive compatibility (IC), strong budget-balance (SBB), and be efficient. On the other hand, important applications to web advertisement, stock exchange, and frequency spectrum allocation, require us to consider two-sided combinatorial auctions in which buyers have preferences on subsets of items, and sellers may offer multiple heterogeneous items. No efficient mechanism was known so far for such two-sided combinatorial markets. This work provides the first IR, IC and SBB mechanisms that provides an O(1)-approximation to the optimal social welfare for two-sided markets. An initial construction yields such a mechanism, but exposes a conceptual problem in the traditional SBB notion. This leads us to define the stronger notion of direct trade strong budget balance (DSBB). We then proceed to design mechanisms that are IR, IC, DSBB, and again provide an O(1)-approximation to the optimal social welfare. Our mechanisms work for any number of buyers with XOS valuations - a class in between submodular and subadditive functions - and any number of sellers. We provide a mechanism that is dominant strategy incentive compatible (DSIC) if the sellers each have one item for sale, and one that is bayesian incentive compatible (BIC) if sellers hold multiple items and have additive valuations over them. Finally, we present a DSIC mechanism for the case that the valuation functions of all buyers and sellers are additive.

Includes members:
  Member "the best of both worlds asymptotically efficient mechanisms with a guarantee on the expected gains from trade":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient two sided markets with limited information")
  Member "approximating gains from trade in two sided markets via simple mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient two sided markets with limited information")
  Member "fixed price approximability of the optimal gain from trade":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "efficient two sided markets with limited information")
  Member "sbba a strongly budget balanced double auction mechanism":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "efficient two sided markets with limited information")
  Member "almost efficient mechanisms for bilateral trading":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "efficient two sided markets with limited information")
  Member "combinatorial auctions via posted prices":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "polymatroid prophet inequalities":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "online stochastic max weight matching prophet inequality for vertex and edge arrival models")
  Member "matroid prophet inequalities":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "predict and match prophet inequalities with uncertain supply")

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)