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: "a note on selling optimally two uniformly distributed goods"
  Abstract: We provide a new, much simplified and straightforward proof to a result of Pavlov [2011] regarding the revenue maximizing mechanism for selling two goods with uniformly i.i.d. valuations over intervals $[c,c+1]$, to an additive buyer. This is done by explicitly defining optimal dual solutions to a relaxed version of the problem, where the convexity requirement for the bidder's utility has been dropped. Their optimality comes directly from their structure, through the use of exact complementarity. For $c=0$ and $c\geq 0.092$ it turns out that the corresponding optimal primal solution is a feasible selling mechanism, thus the initial relaxation comes without a loss, and revenue maximality follows. However, for $0<c<0.092$ that's not the case, providing the first clear example where relaxing convexity provably does not come for free, even in a two-item regularly i.i.d. setting.

Connected through hyperedge HE-1 (induced by source paper "bounding the optimal revenue of selling multiple goods"):
  with members:
    - "approximate revenue maximization with multiple items"
    - "duality and optimality of auctions for uniform distributions"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "an n to 1 bidder reduction for multi item auctions and its applications"
    - "mechanism design via optimal transport"
    - "the menu size complexity of auctions"
    - "the complexity of optimal mechanism design"
    - "simple and nearly optimal multi item auctions"

Connected through hyperedge HE-2 (induced by source paper "duality and optimality of auctions for uniform distributions"):
  with members:
    - "approximate revenue maximization with multiple items"
    - "bounding the optimal revenue of selling multiple goods"
    - "selling two goods optimally"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "optimal mechanisms with simple menus"
    - "mechanism design via optimal transport"
    - "the menu size complexity of auctions"
    - "the complexity of optimal mechanism design"

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)