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: "optimal auctions vs anonymous pricing"
  Abstract: For selling a single item to agents with independent but non-identically distributed values, the revenue optimal auction is complex. With respect to it, Hartline and Rough garden showed that the approximation factor of the second-price auction with an anonymous reserve is between two and four. We consider the more demanding problem of approximating the revenue of the ex ante relaxation of the auction problem by posting an anonymous price (while supplies last) and prove that their worst-case ratio is e. As a corollary, the upper-bound of anonymous pricing or anonymous reserves versus the optimal auction improves from four to e. We conclude that, up to an e factor, discrimination and simultaneity are unimportant for driving revenue in single-item auctions.

Connected through hyperedge HE-1 (induced by source paper "a permutation equivariant neural network architecture for auction design"):
  with members:
    - "settling the sample complexity of single parameter revenue maximization"
    - "a neural architecture for designing truthful and efficient auctions"
    - "multi agent adversarial inverse reinforcement learning"
    - "approximation schemes for a buyer with independent items via symmetries"
    - "tight revenue gaps among simple mechanisms"
    - "a duality based unified approach to bayesian mechanism design"
    - "deep sets"
    - "invariant and equivariant graph networks"

Connected through hyperedge HE-2 (induced by source paper "benchmark design and prior independent optimization"):
  with members:
    - "an end to end argument in mechanism design prior independent auctions for budgeted agents"
    - "randomization beats second price as a prior independent auction"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "optimal competitive auctions"
    - "optimal platform design"
    - "envy freedom and prior free mechanism design"
    - "optimal mechansim design and money burning"
    - "a comparison of performance measures for online algorithms"

Connected through hyperedge HE-3 (induced by source paper "learning reserve prices in second price auctions"):
  with members:
    - "settling the sample complexity of single parameter revenue maximization"
    - "learning optimal reserve price against non myopic bidders"
    - "tight revenue gaps among simple mechanisms"
    - "tight approximation ratio of anonymous pricing"
    - "a general theory of sample complexity for multi item profit maximization"
    - "learning multi item auctions with or without samples"
    - "a sample complexity measure with applications to learning optimal auctions"
    - "simple mechanisms for subadditive buyers via duality"

Connected through hyperedge HE-4 (induced by source paper "optimal auctions vs anonymous pricing beyond linear utility"):
  with members:
    - "tight revenue gaps among simple mechanisms"
    - "tight approximation ratio of anonymous pricing"
    - "prior independent auctions for risk averse agents"
    - "bayesian optimal auctions via multi to single agent reduction"
    - "the simple economics of approximately optimal auctions"
    - "bayesian combinatorial auctions expanding single buyer mechanisms to many buyers"
    - "sequential posted pricing and multi parameter mechanism design"
    - "mechanism design via correlation gap"

Connected through hyperedge HE-5 (induced by source paper "the vickrey auction with a single duplicate bidder approximates the optimal revenue"):
  with members:
    - "99 revenue via enhanced competition"
    - "the competition complexity of auctions a bulow klemperer result for multi dimensional bidders"
    - "randomization beats second price as a prior independent auction"
    - "prior independent mechanisms for scheduling"
    - "vickrey auctions for irregular distributions"

Connected through hyperedge HE-6 (induced by source paper "separation between second price auctions with personalized reserves and the revenue optimal auction"):
  with members:
    - "tight revenue gaps among simple mechanisms"
    - "a field guide to personalized reserve prices"

Connected through hyperedge HE-7 (induced by source paper "tight revenue gaps among simple mechanisms"):
  with members:
    - "prophet secretary through blind strategies"
    - "a duality based unified approach to bayesian mechanism design"
    - "nearly optimal pricing algorithms for production constrained and laminar bayesian selection"
    - "improved approximations for free order prophets and second price auctions"
    - "tight approximation ratio of anonymous pricing"
    - "approximate revenue maximization with multiple items"
    - "prophet secretary surpassing the 1 1 e barrier"
    - "prophet secretary for combinatorial auctions and matroids"

Connected through hyperedge HE-8 (induced by source paper "tight approximation ratio of anonymous pricing"):
  with members:
    - "tight revenue gaps among simple mechanisms"
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "prophet secretary surpassing the 1 1 e barrier"
    - "simple mechanisms for subadditive buyers via duality"
    - "revenue gaps for discriminatory and anonymous sequential posted pricing"
    - "revenue gaps for static and dynamic posted pricing of homogeneous goods"
    - "the menu size complexity of revenue 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)