human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "bayesian optimal auctions via multi to single agent reduction"):
  Abstract: We study an abstract optimal auction problem for a single good or service. This problem includes environments where agents have budgets, risk preferences, or multi-dimensional preferences over several possible configurations of the good (furthermore, it allows an agent's budget and risk preference to be known only privately to the agent). These are the main challenge areas for auction theory. A single-agent problem is to optimize a given objective subject to a constraint on the maximum probability with which each type is allocated, a.k.a., an allocation rule. Our approach is a reduction from multi-agent mechanism design problem to collection of single-agent problems. We focus on maximizing revenue, but our results can be applied to other objectives (e.g., welfare). #R##N#An optimal multi-agent mechanism can be computed by a linear/convex program on interim allocation rules by simultaneously optimizing several single-agent mechanisms subject to joint feasibility of the allocation rules. For single-unit auctions, Border \citeyearpar{B91} showed that the space of all jointly feasible interim allocation rules for $n$ agents is a $\NumTypes$-dimensional convex polytope which can be specified by $2^\NumTypes$ linear constraints, where $\NumTypes$ is the total number of all agents' types. Consequently, efficiently solving the mechanism design problem requires a separation oracle for the feasibility conditions and also an algorithm for ex-post implementation of the interim allocation rules. We show that the polytope of jointly feasible interim allocation rules is the projection of a higher dimensional polytope which can be specified by only $O(\NumTypes^2)$ linear constraints. Furthermore, our proof shows that finding a preimage of the interim allocation rules in the higher dimensional polytope immediately gives an ex-post implementation.

Includes members:
  Member "bayesian combinatorial auctions expanding single buyer mechanisms to many buyers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "an algorithmic characterization of multi dimensional mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "extreme value theorems for optimal multidimensional pricing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "escaping cannibalization correlation robust pricing for a unit demand buyer")
  Member "pricing randomized allocations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "escaping cannibalization correlation robust pricing for a unit demand buyer")
  Member "budget constrained auctions with heterogeneous items":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal mechanisms for selling two items to a single buyer having uniformly distributed valuations")
  Member "algorithmic pricing via virtual valuations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "simple credible and approximately optimal auctions")

Question: Please tell me which class the source paper 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)