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: "bayesian sequential auctions"
  Abstract: In many natural settings agents participate in multiple different auctions that are not simultaneous. In such auctions, future opportunities affect strategic considerations of the players. The goal of this paper is to develop a quantitative understanding of outcomes of such sequential auctions. In earlier work (Paes Leme et al. 2012) we initiated the study of the price of anarchy in sequential auctions. We considered sequential first price auctions in the full information model, where players are aware of all future opportunities, as well as the valuation of all players. In this paper, we study efficiency in sequential auctions in the Bayesian environment, relaxing the informational assumption on the players. We focus on two environments, both studied in the full information model in Paes Leme et al. 2012, matching markets and matroid auctions. In the full information environment, a sequential first price cut auction for matroid settings is efficient. In Bayesian environments this is no longer the case, as we show using a simple example with three players. Our main result is a bound of $1+\frac{e}{e-1}\approx 2.58$ on the price of anarchy in both matroid auctions and single-value matching markets (even with correlated types) and a bound of $2\frac{e}{e-1}\approx 3.16$ for general matching markets with independent types. To bound the price of anarchy we need to consider possible deviations at an equilibrium. In a sequential Bayesian environment the effect of deviations is more complex than in one-shot games; early bids allow others to infer information about the player's value. We create effective deviations despite the presence of this difficulty by introducing a bluffing technique of independent interest.

Connected through hyperedge HE-1 (induced by source paper "online submodular welfare maximization greedy beats 1 2 in random order"):
  with members:
    - "near optimal online algorithms and fast approximation algorithms for resource allocation problems"
    - "randomized composable core sets for distributed submodular maximization"
    - "online submodular welfare maximization greedy is optimal"
    - "geometry of online packing linear programs"
    - "composable and efficient mechanisms"
    - "sequential auctions and externalities"
    - "online vertex weighted bipartite matching and single bid budgeted allocations"
    - "online stochastic matching online actions based on offline statistics"

Connected through hyperedge HE-2 (induced by source paper "the price of anarchy in auctions"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "best response dynamics in combinatorial auctions with item bidding"
    - "simple mechanisms for agents with complements"
    - "the price of anarchy in large games"
    - "on the economic efficiency of the combinatorial clock auction"
    - "on the efficiency of all pay mechanisms"
    - "learning and efficiency in games with dynamic population"
    - "no regret learning in bayesian games"

Connected through hyperedge HE-3 (induced by source paper "simple mechanisms for agents with complements"):
  with members:
    - "simple auctions for agents with complements"
    - "interpolating between truthful and non truthful mechanisms for combinatorial auctions"
    - "the pseudo dimension of near optimal auctions"
    - "greedy algorithms make efficient mechanisms"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "on the complexity of computing an equilibrium in combinatorial auctions"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "an n to 1 bidder reduction for multi item auctions and its applications"

Connected through hyperedge HE-4 (induced by source paper "interpolating between truthful and non truthful mechanisms for combinatorial auctions"):
  with members:
    - "on the complexity of computing an equilibrium in combinatorial auctions"
    - "inapproximability of truthful mechanisms via generalizations of the vc dimension"
    - "clinching auctions beyond hard budget constraints"
    - "price of anarchy for auction revenue"
    - "on the efficiency of the walrasian mechanism"
    - "expressiveness and robustness of first price position auctions"
    - "the computational complexity of truthfulness in combinatorial auctions"
    - "polyhedral clinching auctions and the adwords polytope"

Connected through hyperedge HE-5 (induced by source paper "on the complexity of computing an equilibrium in combinatorial auctions"):
  with members:
    - "economic efficiency requires interaction"
    - "composable and efficient mechanisms"
    - "simultaneous auctions are almost efficient"
    - "sequential auctions and externalities"
    - "non price equilibria in markets of discrete goods"
    - "optimization with demand oracles"
    - "price of anarchy for greedy auctions"
    - "combinatorial auctions with decreasing marginal utilities"

Connected through hyperedge HE-6 (induced by source paper "a unifying hierarchy of valuations with complements and substitutes"):
  with members:
    - "bayesian games and the smoothness framework"
    - "combinatorial auctions with restricted complements"
    - "composable and efficient mechanisms"
    - "simultaneous auctions are almost efficient"
    - "sequential auctions and externalities"
    - "non price equilibria in markets of discrete goods"
    - "price of anarchy for greedy auctions"
    - "combinatorial auctions with decreasing marginal utilities"

Connected through hyperedge HE-7 (induced by source paper "efficient advert assignment"):
  with members:
    - "econometrics for learning agents"
    - "optimising trade offs among stakeholders in ad auctions"
    - "a dynamic axiomatic approach to first price auctions"
    - "simplicity expressiveness tradeoffs in mechanism design"
    - "online advertisement optimization and stochastic networks"
    - "truthful mechanisms with implicit payment computation"
    - "bidding to the top vcg and equilibria of position based auctions"

Connected through hyperedge HE-8 (induced by source paper "welfare guarantees for proportional allocations"):
  with members:
    - "efficiency guarantees in auctions with budgets"
    - "bounding the inefficiency of outcomes in generalized second price auctions"
    - "bayesian games and the smoothness framework"
    - "composable and efficient mechanisms"
    - "simultaneous auctions are almost efficient"

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)