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: "fixed price approximability of the optimal gain from trade"
  Abstract: Bilateral trade is a fundamental economic scenario comprising a strategically acting buyer and seller, each holding valuations for the item, drawn from publicly known distributions. A mechanism is supposed to facilitate trade between these agents, if such trade is beneficial. It was recently shown that the only mechanisms that are simultaneously DSIC, SBB, and ex-post IR, are fixed price mechanisms, i.e., mechanisms that are parametrised by a price p, and trade occurs if and only if the valuation of the buyer is at least p and the valuation of the seller is at most p. The gain from trade is the increase in welfare that results from applying a mechanism; here we study the gain from trade achievable by fixed price mechanisms. We explore this question for both the bilateral trade setting, and a double auction setting where there are multiple buyers and sellers. We first identify a fixed price mechanism that achieves a gain from trade of at least 2/r times the optimum, where r is the probability that the seller's valuation does not exceed the buyer's valuation. This extends a previous result by McAfee. Subsequently, we improve this approximation factor in an asymptotic sense, by showing that a more sophisticated rule for setting the fixed price results in an expected gain from trade within a factor O(log(1/r)) of the optimal gain from trade. This is asymptotically the best approximation factor possible. Lastly, we extend our study of fixed price mechanisms to the double auction setting defined by a set of multiple i.i.d. unit demand buyers, and i.i.d. unit supply sellers. We present a fixed price mechanism that achieves a gain from trade that achieves for all epsilon > 0 a gain from trade of at least (1-epsilon) times the expected optimal gain from trade with probability 1 - 2/e^{#T epsilon^2 /2}, where #T is the expected number of trades resulting from the double auction.

Connected through hyperedge HE-1 (induced by source paper "efficient two sided markets with limited information"):
  with members:
    - "optimal single choice prophet inequalities from samples"
    - "bulow klemperer style results for welfare maximization in two sided markets"
    - "improved truthful mechanisms for combinatorial auctions with submodular bidders"
    - "online trading as a secretary problem"
    - "the best of both worlds asymptotically efficient mechanisms with a guarantee on the expected gains from trade"
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "online market intermediation"
    - "sbba a strongly budget balanced double auction mechanism"

Connected through hyperedge HE-2 (induced by source paper "multi unit bilateral trade"):
  with members:
    - "online trading as a secretary problem"
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "muda a truthful multi unit double auction mechanism"
    - "online market intermediation"
    - "almost efficient mechanisms for bilateral trading"
    - "online truthful mechanisms for multi sided markets"
    - "simple and near optimal mechanisms for market intermediation"

Connected through hyperedge HE-3 (induced by source paper "online trading as a secretary problem"):
  with members:
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "online market intermediation"
    - "sbba a strongly budget balanced double auction mechanism"
    - "combinatorial auctions via posted prices"
    - "algorithms for secretary problems on graphs and hypergraphs"

Connected through hyperedge HE-4 (induced by source paper "cost sharing in two sided markets"):
  with members:
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "two sided facility location"
    - "combinatorial cost sharing"
    - "cost recovering bayesian algorithmic mechanism design"
    - "the cooperative game theory foundations of network bargaining games"

Connected through hyperedge HE-5 (induced by source paper "double auctions in markets for multiple kinds of goods"):
  with members:
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "polyhedral clinching auctions for two sided markets"
    - "approximately efficient two sided combinatorial auctions"
    - "the pseudo dimension of near optimal auctions"
    - "on random sampling auctions for digital goods"
    - "prior independent mechanisms for scheduling"
    - "ascending auctions and walrasian equilibrium"
    - "envy freedom and prior free mechanism design"

Connected through hyperedge HE-6 (induced by source paper "approximately efficient two sided combinatorial auctions"):
  with members:
    - "the best of both worlds asymptotically efficient mechanisms with a guarantee on the expected gains from trade"
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "sbba a strongly budget balanced double auction mechanism"
    - "almost efficient mechanisms for bilateral trading"
    - "combinatorial auctions via posted prices"
    - "polymatroid prophet inequalities"
    - "matroid prophet inequalities"

Connected through hyperedge HE-7 (induced by source paper "almost efficient mechanisms for bilateral trading"):
  with members:
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "auctions with severely bounded communication"

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)