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: "computational efficiency requires simple taxation"
  Abstract: We characterize the communication complexity of truthful mechanisms. Our departure point is the well known taxation principle. The taxation principle asserts that every truthful mechanism can be interpreted as follows: every player is presented with a menu that consists of a price for each bundle (the prices depend only on the valuations of the other players). Each player is allocated a bundle that maximizes his profit according to this menu. We define the taxation complexity of a truthful mechanism to be the logarithm of the maximum number of menus that may be presented to a player. #R##N#Our main finding is that in general the taxation complexity essentially equals the communication complexity. The proof consists of two main steps. First, we prove that for rich enough domains the taxation complexity is at most the communication complexity. We then show that the taxation complexity is much smaller than the communication complexity only in "pathological" cases and provide a formal description of these extreme cases. #R##N#Next, we study mechanisms that access the valuations via value queries only. In this setting we establish that the menu complexity -- a notion that was already studied in several different contexts -- characterizes the number of value queries that the mechanism makes in exactly the same way that the taxation complexity characterizes the communication complexity. #R##N#Our approach yields several applications, including strengthening the solution concept with low communication overhead, fast computation of prices, and hardness of approximation by computationally efficient truthful mechanisms.

Connected through hyperedge HE-1 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders"):
  with members:
    - "complement free couples must communicate a hardness result for two player combinatorial auctions"
    - "beyond 1 2 approximation for submodular maximization on massive data streams"
    - "prophet secretary for combinatorial auctions and matroids"
    - "on simultaneous two player combinatorial auctions"
    - "combinatorial auctions do need modest interaction"
    - "breaking the logarithmic barrier for truthful combinatorial auctions with submodular bidders"
    - "online matroid intersection beating half for random arrival"
    - "inapproximability of truthful mechanisms via generalizations of the vc dimension"

Connected through hyperedge HE-2 (induced by source paper "implementation in advised strategies welfare guarantees from posted price mechanisms when demand queries are np hard"):
  with members:
    - "submodular maximization beyond non negativity guarantees fast algorithms and applications"
    - "guess free maximization of submodular and linear sums"
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"
    - "breaking the logarithmic barrier for truthful combinatorial auctions with submodular bidders"
    - "inapproximability of truthful mechanisms via generalizations of the vc dimension"
    - "combinatorial auctions via posted prices"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"
    - "the computational complexity of truthfulness in combinatorial auctions"

Connected through hyperedge HE-3 (induced by source paper "combinatorial auctions do need modest interaction"):
  with members:
    - "on estimating maximum matching size in graph streams"
    - "on simultaneous two player combinatorial auctions"
    - "best response dynamics in combinatorial auctions with item bidding"
    - "welfare maximization with limited interaction"
    - "combinatorial auctions via posted prices"
    - "economic efficiency requires interaction"
    - "simultaneous auctions are almost efficient"
    - "learning valuation functions"

Connected through hyperedge HE-4 (induced by source paper "economic efficiency requires interaction"):
  with members:
    - "on simultaneous two player combinatorial auctions"
    - "combinatorial auctions do need modest interaction"
    - "welfare maximization with limited interaction"
    - "on the efficiency of the walrasian mechanism"
    - "the computational complexity of truthfulness in combinatorial auctions"
    - "better bounds for matchings in the streaming model"
    - "simultaneous auctions are almost efficient"
    - "limitations of randomized mechanisms for combinatorial auctions"

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)