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: "truth revelation in approximately efficient combinatorial auctions"
  Abstract: Some important classical mechanisms considered in Microeconomics and Game Theory require the solution of a difficult optimization problem. This is true of mechanisms for combinatorial auctions, which have in recent years assumed practical importance, and in particular of the gold standard for combinatorial auctions, the Generalized Vickrey Auction (GVA). Traditional analysis of these mechanisms - in particular, their truth revelation properties - assumes that the optimization problems are solved precisely. In reality, these optimization problems can usually be solved only in an approximate fashion. We investigate the impact on such mechanisms of replacing exact solutions by approximate ones. Specifically, we look at a particular greedy optimization method. We show that the GVA payment scheme does not provide for a truth revealing mechanism. We introduce another scheme that does guarantee truthfulness for a restricted class of players. We demonstrate the latter property by identifying natural properties for combinatorial auctions and showing that, for our restricted class of players, they imply that truthful strategies are dominant. Those properties have applicability beyond the specific auction studied.

Connected through hyperedge HE-1 (induced by source paper "faithful implementations of distributed algorithms and control laws"):
  with members:
    - "optimal coordinated planning amongst self interested agents with private state"
    - "computationally feasible vcg mechanisms"

Connected through hyperedge HE-2 (induced by source paper "on approximate welfare and revenue maximizing equilibria for size interchangeable bidders"):
  with members:
    - "envy free pricing in multi unit markets"
    - "envy free pricing in large markets approximating revenue and welfare"

Connected through hyperedge HE-3 (induced by source paper "computational efficiency requires simple taxation"):
  with members:
    - "breaking the logarithmic barrier for truthful combinatorial auctions with submodular bidders"
    - "inapproximability of truthful mechanisms via generalizations of the vc dimension"
    - "economic efficiency requires interaction"
    - "multi parameter mechanisms with implicit payment computation"
    - "the menu size complexity of auctions"
    - "the computational complexity of truthfulness in combinatorial auctions"
    - "from convex optimization to randomized mechanisms toward optimal combinatorial auctions"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"

Connected through hyperedge HE-4 (induced by source paper "setting lower bounds on truthfulness"):
  with members:
    - "the vcg mechanism for bayesian scheduling"
    - "inapproximability of truthful mechanisms via generalizations of the vc dimension"
    - "bayesian truthful mechanisms for job scheduling from bi criterion approximation algorithms"
    - "copula based randomized mechanisms for truthful scheduling on two unrelated machines"
    - "prior independent mechanisms for scheduling"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"
    - "the power of randomness in bayesian optimal mechanism design"
    - "mechanisms for multi unit auctions"

Connected through hyperedge HE-5 (induced by source paper "non optimal mechanism design"):
  with members:
    - "understanding incentives mechanism design becomes algorithm design"
    - "on the efficiency of the walrasian mechanism"
    - "composable and efficient mechanisms"
    - "sequential posted pricing and multi parameter mechanism design"
    - "bayesian incentive compatibility via fractional assignments"
    - "budget constrained auctions with heterogeneous items"
    - "price of anarchy for greedy auctions"
    - "algorithmic pricing via virtual valuations"

Connected through hyperedge HE-6 (induced by source paper "a pac approach to application specific algorithm selection"):
  with members:
    - "the pseudo dimension of near optimal auctions"
    - "a bayesian approach to tackling hard computational problems"
    - "learning theory and algorithms for revenue optimization in second price auctions with reserve"
    - "algorithm runtime prediction methods evaluation"
    - "self improving algorithms for coordinate wise maxima"
    - "satzilla portfolio based algorithm selection for sat"

Connected through hyperedge HE-7 (induced by source paper "virtualization of 5g cellular networks as a hierarchical combinatorial auction"):
  with members:
    - "5g cellular key enabling technologies and research challenges"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "massive mimo for next generation wireless systems"
    - "a dynamic embedding algorithm for wireless network virtualization"

Connected through hyperedge HE-8 (induced by source paper "on welfare approximation and stable pricing"):
  with members:
    - "combinatorial walrasian equilibrium"
    - "envy multi envy and revenue maximization"
    - "combinatorial auctions with decreasing marginal utilities"

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)