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 "limitations of randomized mechanisms for combinatorial auctions"):
  Abstract: Recently, a randomized mechanism has been discovered [Dughmi, Roughgarden and Yan; STOC'11] for combinatorial auctions that is truthful in expectation and guarantees a (1-1/e)-approximation to the optimal social welfare when players have coverage valuations. This approximation ratio is the best possible even for non-truthful algorithms, assuming $P \neq NP$. Given the recent sequence of negative results for combinatorial auctions under more restrictive notions of incentive compatibility, this development raises a natural question: Are truthful-in-expectation mechanisms compatible with polynomial-time approximation in a way that deterministic or universally truthful mechanisms are not? In particular, can polynomial-time truthful-in-expectation mechanisms guarantee a near-optimal approximation ratio for more general variants of combinatorial auctions? #R##N#We prove that this is not the case. Specifically, the result of Dughmi, Roughgarden and Yan cannot be extended to combinatorial auctions with submodular valuations in the value oracle model. (Absent strategic considerations, a (1-1/e)-approximation is still achievable in this setting.) More precisely, we prove that there is a constant \gamma>0 such that there is no randomized mechanism that is truthful-in-expectation--- or even approximately truthful-in-expectation --- and guarantees an m^{-\gamma}-approximation to the optimal social welfare for combinatorial auctions with submodular valuations in the value oracle model. We also prove an analogous result for the flexible combinatorial public projects (CPP) problem. Both our results present an unexpected separation between coverage functions and submodular functions, which does not occur for these problems without strategic considerations.

Includes members:
  Member "the computational complexity of truthfulness in combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "symmetry and approximability of submodular maximization problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximability of monotone submodular function maximization under cardinality and matroid constraints in the streaming model")
  Member "a truthful randomized mechanism for combinatorial public projects via convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "a truthful mechanism for the generalized assignment problem")
  Member "from convex optimization to randomized mechanisms toward optimal combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "an impossibility result for truthful combinatorial auctions with submodular valuations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "truthfulness via proxies":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a bridge between liquid and social welfare in combinatorial auctions with submodular bidders")
  Member "submodular maximization by simulated annealing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimal streaming algorithms for submodular maximization with cardinality constraints")

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)