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: "selling two goods optimally"
  Abstract: We provide sufficient conditions for revenue maximization in a two-good monopoly where the buyer's values for the items come from independent (but not necessarily identical) distributions over bounded intervals. Under certain distributional assumptions, we give exact, closed-form formulas for the prices and allocation rule of the optimal selling mechanism. As a side result we give the first example of an optimal mechanism in an i.i.d. setting over a support of the form $[0,b]$ which is not deterministic. Since our framework is based on duality techniques, we were also able to demonstrate how slightly relaxed versions of it can still be used to design mechanisms that have very good approximation ratios with respect to the optimal revenue, through a "convexification" process.

Connected through hyperedge HE-1 (induced by source paper "optimal mechanisms for selling two items to a single buyer having uniformly distributed valuations"):
  with members:
    - "on optimal mechanisms in the two item single buyer unit demand setting"
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "simple mechanisms for subadditive buyers via duality"
    - "the menu size complexity of revenue approximation"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "optimal auctions with restricted allocations"
    - "bounding the optimal revenue of selling multiple goods"

Connected through hyperedge HE-2 (induced by source paper "on optimal mechanisms in the two item single buyer unit demand setting"):
  with members:
    - "optimal mechanisms for selling two items to a single buyer having uniformly distributed valuations"
    - "a duality based unified approach to bayesian mechanism design"
    - "simple mechanisms for subadditive buyers via duality"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "optimal auctions with restricted allocations"
    - "duality and optimality of auctions for uniform distributions"
    - "strong duality for a multiple good monopolist"
    - "an n to 1 bidder reduction for multi item auctions and its applications"

Connected through hyperedge HE-3 (induced by source paper "a duality based unified approach to bayesian mechanism design"):
  with members:
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "approximate revenue maximization with multiple items"
    - "the value of information concealment"
    - "simple mechanisms for subadditive buyers via duality"
    - "revenue maximization and ex post budget constraints"
    - "the competition complexity of auctions a bulow klemperer result for multi dimensional bidders"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "mechanism design for subadditive agents via an ex ante relaxation"

Connected through hyperedge HE-4 (induced by source paper "optimal mechanism design with risk loving agents"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "revenue maximization with an uncertainty averse buyer"
    - "energy coupon a mean field game perspective on demand response in smart grids"
    - "duality and optimality of auctions for uniform distributions"
    - "strong duality for a multiple good monopolist"
    - "mechanism design via optimal transport"
    - "prior independent auctions for risk averse agents"
    - "mechanisms for risk averse agents without loss"

Connected through hyperedge HE-5 (induced by source paper "optimal auctions through deep learning"):
  with members:
    - "automatic chemical design using a data driven continuous representation of molecules"
    - "approximate revenue maximization with multiple items"
    - "can deep reinforcement learning solve erdos selfridge spencer games"
    - "a sample complexity measure with applications to learning optimal auctions"
    - "simple mechanisms for subadditive buyers via duality"
    - "learning simple auctions"
    - "efficient empirical revenue maximization in single parameter auction environments"
    - "the sample complexity of revenue maximization"

Connected through hyperedge HE-6 (induced by source paper "bounds on the menu size of approximately optimal auctions via optimal transport duality"):
  with members:
    - "the menu complexity of one and a half dimensional mechanism design"
    - "the menu size complexity of revenue approximation"
    - "optimal auctions with restricted allocations"
    - "duality and optimality of auctions for uniform distributions"
    - "sampling and representation complexity of revenue maximization"
    - "strong duality for a multiple good monopolist"
    - "mechanism design via optimal transport"
    - "the menu size complexity of auctions"

Connected through hyperedge HE-7 (induced by source paper "the competition complexity of auctions a bulow klemperer result for multi dimensional bidders"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "simple mechanisms for subadditive buyers via duality"
    - "learning simple auctions"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "the sample complexity of revenue maximization"
    - "the sample complexity of auctions with side information"

Connected through hyperedge HE-8 (induced by source paper "simple mechanisms for subadditive buyers via duality"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "approximate revenue maximization with multiple items"
    - "the competition complexity of auctions a bulow klemperer result for multi dimensional bidders"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "online contention resolution schemes"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"

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)