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: "an algorithmic characterization of multi dimensional mechanisms"
  Abstract: We obtain a characterization of feasible, Bayesian, multi-item multi-bidder auctions with independent, additive bidders as distributions over hierarchical mechanisms. Combined with cyclic-monotonicity our results provide a complete characterization of feasible, Bayesian Incentive Compatible (BIC) auctions for this setting. #R##N#Our characterization is enabled by a novel, constructive proof of Border's theorem, and a new generalization of this theorem to independent (but not necessarily iid) bidders. For one item and independent bidders, we show that any feasible reduced form auction can be implemented as a distribution over hierarchical mechanisms. We also give a polytime algorithm for determining feasibility of a reduced form, or finding a separation hyperplane from feasible reduced forms. Finally, we provide polytime algorithms to find and exactly sample from a distribution over hierarchical mechanisms consistent with a given feasible reduced form. #R##N#Our results generalize to multi-item reduced forms for independent, additive bidders. For multiple items, additive bidders with hard demand constraints, and arbitrary value correlation across items or bidders, we give a proper generalization of Border's theorem, and characterize feasible reduced forms as multicommodity flows in related multicommodity flow instances. We show that our generalization holds for a broader class of feasibility constraints, including intersections of any two matroids. #R##N#As a corollary we obtain revenue-optimal, BIC mechanisms in multi-item multi-bidder settings, when each bidder has arbitrarily correlated values over the items and additive valuations over bundles, and bidders are independent. Their runtime is polynomial in the total number of bidder types (instead of type profiles), and is improved to poly(#items, #bidders) using recent structural results on optimal BIC auctions in item-symmetric settings.

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 "complexity theory game theory and economics the barbados lectures"):
  with members:
    - "a round collapse theorem for computationally sound protocols or tfnp is hard on average in pessiland"
    - "on communication complexity of fixed point computation"
    - "near optimal communication lower bounds for approximate nash equilibria"
    - "query to communication lifting for bpp"
    - "lifting randomized query complexity to randomized communication complexity"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "communication complexity of approximate nash equilibria"
    - "the price of anarchy in auctions"

Connected through hyperedge HE-3 (induced by source paper "the complexity of contracts"):
  with members:
    - "delegated search approximates efficient search"
    - "a duality based unified approach to bayesian mechanism design"
    - "simple versus optimal contracts"
    - "bernoulli factories and black box reductions in mechanism design"
    - "the menu size complexity of revenue approximation"
    - "algorithmic bayesian persuasion"
    - "mixture selection mechanism design and signaling"
    - "non optimal mechanism design"

Connected through hyperedge HE-4 (induced by source paper "optimal mechanism design for single minded agents"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "optimal multi unit mechanisms with private demands"
    - "the menu complexity of one and a half dimensional mechanism design"
    - "the menu size complexity of revenue approximation"
    - "optimal mechanisms with simple menus"
    - "mechanism design via optimal transport"

Connected through hyperedge HE-5 (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-6 (induced by source paper "an efficient e bic to bic transformation and its application to black box reduction in revenue maximization"):
  with members:
    - "multi item mechanisms without item independence learnability via robustness"
    - "the complexity of black box mechanism design with priors"
    - "approximation schemes for a buyer with independent items via symmetries"
    - "a duality based unified approach to bayesian mechanism design"
    - "bernoulli factories and black box reductions in mechanism design"
    - "simple mechanisms for subadditive buyers via duality"
    - "revenue maximization and ex post budget constraints"
    - "mechanism design for subadditive agents via an ex ante relaxation"

Connected through hyperedge HE-7 (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"
    - "selling two goods optimally"
    - "duality and optimality of auctions for uniform distributions"
    - "strong duality for a multiple good monopolist"

Connected through hyperedge HE-8 (induced by source paper "approximation schemes for a unit demand buyer with independent items via symmetries"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "optimal deterministic mechanisms for an additive buyer"
    - "approximate revenue maximization with multiple items"
    - "the menu complexity of one and a half dimensional mechanism design"
    - "simple mechanisms for subadditive buyers via duality"
    - "the menu size complexity of revenue approximation"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "settling the complexity of computing approximate two player nash equilibria"

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)