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: "welfare and profit maximization with production costs"
  Abstract: Combinatorial Auctions are a central problem in Algorithmic Mechanism Design: pricing and allocating goods to buyers with complex preferences in order to maximize some desired objective (e.g., social welfare, revenue, or profit). The problem has been well-studied in the case of limited supply (one copy of each item), and in the case of digital goods (the seller can produce additional copies at no cost). Yet in the case of resources---oil, labor, computing cycles, etc.---neither of these abstractions is just right: additional supplies of these resources can be found, but at increasing difficulty (marginal cost) as resources are depleted. #R##N#In this work, we initiate the study of the algorithmic mechanism design problem of combinatorial pricing under increasing marginal cost. The goal is to sell these goods to buyers with unknown and arbitrary combinatorial valuation functions to maximize either the social welfare, or the seller's profit; specifically we focus on the setting of \emph{posted item prices} with buyers arriving online. We give algorithms that achieve {\em constant factor} approximations for a class of natural cost functions---linear, low-degree polynomial, logarithmic---and that give logarithmic approximations for more general increasing marginal cost functions (along with a necessary additive loss). We show that these bounds are essentially best possible for these settings.

Connected through hyperedge HE-1 (induced by source paper "reducing inefficiency in carbon auctions with imperfect competition"):
  with members:
    - "welfare maximization with production costs a primal dual approach"
    - "sequential auctions and externalities"

Connected through hyperedge HE-2 (induced by source paper "online primal dual algorithms with configuration linear programs"):
  with members:
    - "online covering with sum of ell_q norm objectives"
    - "online submodular maximization with preemption"
    - "online contention resolution schemes"
    - "welfare maximization with production costs a primal dual approach"
    - "tight bounds for online vector scheduling"
    - "selfishmigrate a scalable algorithm for non clairvoyantly scheduling heterogeneous processors"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"
    - "online primal dual for non linear optimization with applications to speed scaling"

Connected through hyperedge HE-3 (induced by source paper "online covering with sum of ell_q norm objectives"):
  with members:
    - "welfare maximization with production costs a primal dual approach"
    - "online packing and covering framework with convex objectives"
    - "approximating sparse covering integer programs online"

Connected through hyperedge HE-4 (induced by source paper "price doubling and item halving robust revenue guarantees for item pricing"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "simple mechanisms for subadditive buyers via duality"
    - "envy free pricing in multi unit markets"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "pricing to maximize revenue and welfare simultaneously in large markets"
    - "on the computational complexity of optimal simple mechanisms"
    - "on welfare approximation and stable pricing"
    - "secretary problems with non uniform arrival order"

Connected through hyperedge HE-5 (induced by source paper "multidimensional dynamic pricing for welfare maximization"):
  with members:
    - "do prices coordinate markets"
    - "bandit convex optimization sqrt t regret in one dimension"
    - "watch and learn optimizing from revealed preferences feedback"
    - "learning economic parameters from revealed preferences"
    - "online learning and profit maximization from revealed preferences"
    - "combinatorial auctions via posted prices"
    - "bandits with knapsacks"
    - "efficiently learning from revealed preference"

Connected through hyperedge HE-6 (induced by source paper "pricing to maximize revenue and welfare simultaneously in large markets"):
  with members:
    - "do prices coordinate markets"
    - "the sample complexity of revenue maximization"
    - "envy free pricing in large markets approximating revenue and welfare"
    - "applications of alpha strongly regular distributions to bayesian auctions"
    - "optimising trade offs among stakeholders in ad auctions"
    - "on the ratio of revenue to welfare in single parameter mechanism design"
    - "pricing ad slots with consecutive multi unit demand"
    - "efficiency revenue trade offs in auctions"

Connected through hyperedge HE-7 (induced by source paper "posted pricing sans discrimination"):
  with members:
    - "do prices coordinate markets"
    - "on the computational complexity of optimal simple mechanisms"
    - "on welfare approximation and stable pricing"
    - "the invisible hand of dynamic market pricing"
    - "sequential posted price mechanisms with correlated valuations"
    - "welfare maximization with production costs a primal dual approach"
    - "combinatorial auctions via posted prices"
    - "combinatorial walrasian equilibrium"

Connected through hyperedge HE-8 (induced by source paper "online convex covering and packing problems"):
  with members:
    - "welfare maximization with production costs a primal dual approach"
    - "online covering with convex objectives and applications"
    - "online packing and covering framework with convex objectives"
    - "approximating sparse covering integer programs online"
    - "online primal dual for non linear optimization with applications to speed scaling"

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)