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: "randomization beats second price as a prior independent auction"
  Abstract: Designing revenue optimal auctions for selling an item to $n$ symmetric bidders is a fundamental problem in mechanism design. Myerson (1981) shows that the second price auction with an appropriate reserve price is optimal when bidders' values are drawn i.i.d. from a known regular distribution. A cornerstone in the prior-independent revenue maximization literature is a result by Bulow and Klemperer (1996) showing that the second price auction without a reserve achieves $(n-1)/n$ of the optimal revenue in the worst case. #R##N#We construct a randomized mechanism that strictly outperforms the second price auction in this setting. Our mechanism inflates the second highest bid with a probability that varies with $n$. For two bidders we improve the performance guarantee from $0.5$ to $0.512$ of the optimal revenue. We also resolve a question in the design of revenue optimal mechanisms that have access to a single sample from an unknown distribution. We show that a randomized mechanism strictly outperforms all deterministic mechanisms in terms of worst case guarantee.

Connected through hyperedge HE-1 (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"
    - "optimal auctions vs anonymous pricing"
    - "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-2 (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-3 (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"
    - "optimal auctions vs anonymous pricing"
    - "prior independent mechanisms for scheduling"
    - "vickrey auctions for irregular distributions"

Connected through hyperedge HE-4 (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-5 (induced by source paper "an end to end argument in mechanism design prior independent auctions for budgeted agents"):
  with members:
    - "a b testing of auctions"
    - "the price of anarchy in auctions"
    - "approximate revenue maximization in interdependent value settings"
    - "mechanism design for data science"
    - "simple and near optimal mechanisms for market intermediation"
    - "price of anarchy for auction revenue"
    - "efficiency guarantees in auctions with budgets"
    - "prior independent mechanisms for scheduling"

Connected through hyperedge HE-6 (induced by source paper "optimal pricing for mhr distributions"):
  with members:
    - "tight revenue gaps among simple mechanisms"
    - "online market intermediation"
    - "revenue gaps for discriminatory and anonymous sequential posted pricing"
    - "the vcg mechanism for bayesian scheduling"
    - "optimal auctions vs anonymous pricing"
    - "bayesian combinatorial auctions expanding single buyer mechanisms to many buyers"
    - "extreme value theorems for optimal multidimensional pricing"
    - "mechanism design via correlation gap"

Connected through hyperedge HE-7 (induced by source paper "are two samples really better than one on the non asymptotic performance of empirical revenue maximization"):
  with members:
    - "a general theory of sample complexity for multi item profit maximization"
    - "learning simple auctions"
    - "efficient empirical revenue maximization in single parameter auction environments"
    - "sample complexity of automated mechanism design"
    - "the sample complexity of revenue maximization"
    - "online learning in repeated auctions"
    - "making the most of your samples"

Connected through hyperedge HE-8 (induced by source paper "how to manipulate truthful prior dependent mechanisms"):
  with members:
    - "perfect bayesian equilibria in repeated sales"
    - "prior independent auctions for risk averse agents"
    - "an algorithmic characterization of multi dimensional mechanisms"

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)