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 "a truthful mechanism for the generalized assignment problem"):
  Abstract: We propose a truthful-in-expectation, $(1-1/e)$-approximation mechanism for a strategic variant of the generalized assignment problem (GAP). In GAP, a set of items has to be optimally assigned to a set of bins without exceeding the capacity of any singular bin. In the strategic variant of the problem we study, values for assigning items to bins are the private information of bidders and the mechanism should provide bidders with incentives to truthfully report their values. The approximation ratio of the mechanism is a significant improvement over the approximation ratio of the existing truthful mechanism for GAP. #R##N#The proposed mechanism comprises a novel convex optimization program as the allocation rule as well as an appropriate payment rule. To implement the convex program in polynomial time, we propose a fractional local search algorithm which approximates the optimal solution within an arbitrarily small error leading to an approximately truthful-in-expectation mechanism. The presented algorithm improves upon the existing optimization algorithms for GAP in terms of simplicity and runtime while the approximation ratio closely matches the best approximation ratio given for GAP when all inputs are publicly known.

Includes members:
  Member "breaking the logarithmic barrier for truthful combinatorial auctions with submodular bidders":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "the computational complexity of truthfulness in combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "bayesian combinatorial auctions expanding single buyer mechanisms to many buyers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "limitations of randomized mechanisms for combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "a truthful randomized mechanism for combinatorial public projects via convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "probabilistic verification for obviously strategyproof mechanisms")
  Member "an approximately truthful in expectation mechanism for combinatorial auctions using value queries":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards more practical linear programming based techniques for algorithmic mechanism design")
  Member "from convex optimization to randomized mechanisms toward optimal combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "truthful assignment without money":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "bounded incentives in manipulating the probabilistic serial rule")

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)