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: "clearing markets via bundles"
  Abstract: We study algorithms for combinatorial market design problems, where a set of heterogeneous and indivisible objects are priced and sold to potential buyers subject to equilibrium constraints. Extending the CWE notion introduced by Feldman et al. [STOC 2013], we introduce the concept of a Market-Clearing Combinatorial Walrasian Equilibium (MC-CWE) as a natural relaxation of the classical Walrasian equilibrium (WE) solution concept. The only difference between a MC-CWE and a WE is the ability for the seller to bundle the items prior to sale. This innocuous and natural bundling operation imposes a plethora of algorithmic and economic challenges and opportunities. Unlike WE, which is guaranteed to exist only for (gross) substitutes valuations, a MC-CWE always exists. The main algorithmic challenge, therefore, is to design computationally efficient mechanisms that generate MC-CWE outcomes that approximately maximize social welfare. For a variety of valuation classes encompassing substitutes and complements (including super-additive, single-minded and budget-additive valuations), we design polynomial-time MC-CWE mechanisms that provide tight welfare approximation results.

Connected through hyperedge HE-1 (induced by source paper "on the power and limits of dynamic pricing in combinatorial markets"):
  with members:
    - "a general framework for endowment effects in combinatorial markets"
    - "combinatorial auctions with endowment effect"
    - "max min greedy matching"
    - "pricing for online resource allocation intervals and paths"
    - "pricing multi unit markets"
    - "makespan minimization via posted prices"
    - "price doubling and item halving robust revenue guarantees for item pricing"
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"

Connected through hyperedge HE-2 (induced by source paper "a general framework for endowment effects in combinatorial markets"):
  with members:
    - "combinatorial auctions with endowment effect"
    - "on welfare approximation and stable pricing"
    - "welfare and revenue guarantees for competitive bundling equilibrium"
    - "combinatorial walrasian equilibrium"
    - "combinatorial auctions with decreasing marginal utilities"

Connected through hyperedge HE-3 (induced by source paper "to give or not to give fair division for single minded valuations"):
  with members:
    - "fair and square cake cutting in two dimensions"
    - "envy free cake cutting in two dimensions"
    - "characterization and computation of equilibria for indivisible goods"
    - "a discrete and bounded envy free cake cutting protocol for four agents"
    - "a unifying hierarchy of valuations with complements and substitutes"
    - "the complexity of fairness through equilibrium"

Connected through hyperedge HE-4 (induced by source paper "welfare and revenue guarantees for competitive bundling equilibrium"):
  with members:
    - "combinatorial walrasian equilibrium"
    - "mechanisms for multi unit auctions"
    - "combinatorial auctions with decreasing marginal utilities"

Connected through hyperedge HE-5 (induced by source paper "combinatorial walrasian equilibrium"):
  with members:
    - "welfare and revenue guarantees for competitive bundling equilibrium"
    - "combinatorial auctions via posted prices"
    - "understanding incentives mechanism design becomes algorithm design"
    - "lower bound for envy free and truthful makespan approximation on related machines"
    - "optimization with demand oracles"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"
    - "bayesian incentive compatibility via fractional assignments"
    - "envy free makespan approximation"

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)