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 "on the power and limits of dynamic pricing in combinatorial markets"):
  Abstract: We study the power and limits of optimal dynamic pricing in combinatorial markets; i.e., dynamic pricing that leads to optimal social welfare. Previous work by Cohen-Addad et al. [EC'16] demonstrated the existence of optimal dynamic prices for unit-demand buyers, and showed a market with coverage valuations that admits no such prices. However, finding the frontier of markets (i.e., valuation functions) that admit optimal dynamic prices remains an open problem. In this work we establish positive and negative results that narrow the existing gap. #R##N#On the positive side, we provide tools for handling markets beyond unit-demand valuations. In particular, we characterize all optimal allocations in multi-demand markets. This characterization allows us to partition the items into equivalence classes according to the role they play in achieving optimality. Using these tools, we provide a poly-time optimal dynamic pricing algorithm for up to $3$ multi-demand buyers. #R##N#On the negative side, we establish a maximal domain theorem, showing that for every non-gross substitutes valuation, there exist unit-demand valuations such that adding them yields a market that does not admit an optimal dynamic pricing. This result is reminiscent of the seminal maximal domain theorem by Gul and Stacchetti [JET'99] for Walrasian equilibrium. Yang [JET'17] discovered an error in their original proof, and established a different, incomparable version of their maximal domain theorem. En route to our maximal domain theorem for optimal dynamic pricing, we provide the first complete proof of the original theorem by Gul and Stacchetti.

Includes members:
  Member "a general framework for endowment effects in combinatorial markets":
    also connected through other hyperedges:
      (none)
  Member "combinatorial auctions with endowment effect":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a general framework for endowment effects in combinatorial markets")
  Member "max min greedy matching":
    also connected through other hyperedges:
      (none)
  Member "pricing for online resource allocation intervals and paths":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal single choice prophet inequalities from samples")
  Member "pricing multi unit markets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cost sharing over combinatorial domains complement free cost functions and beyond")
  Member "makespan minimization via posted prices":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "prophet inequality for bipartite matching merits of being simple and non adaptive")
  Member "price doubling and item halving robust revenue guarantees for item pricing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "tight revenue gaps among simple mechanisms")
  Member "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)