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 "combinatorial auctions with interdependent valuations sos to the rescue"):
  Abstract: We study combinatorial auctions with interdependent valuations. In such settings, each agent $i$ has a private signal $s_i$ that captures her private information, and the valuation function of every agent depends on the entire signal profile, ${\bs}=(s_1,\ldots,s_n)$. Previous results in economics concentrated on identifying (often stringent) assumptions under which optimal solutions can be attained. The computer science literature provided approximation results for simple single-parameter settings (mostly single item auctions, or matroid feasibility constraints). Both bodies of literature considered only valuations satisfying a technical condition termed {\em single crossing} (or variants thereof). Indeed, without imposing assumptions on the valuations, strong impossibility results exist. #R##N#We consider the class of {\em submodular over signals} (SOS) valuations (without imposing any single-crossing type assumption), and provide the first welfare approximation guarantees for multi-dimensional combinatorial auctions, achieved by universally ex-post IC-IR mechanisms. Our main results are: $(i)$ 4-approximation for any single-parameter downward-closed setting with single-dimensional signals and SOS valuations; $(ii)$ 4-approximation for any combinatorial auction with multi-dimensional signals and {\em separable}-SOS valuations; and $(iii)$ $(k+3)$- and $(2\log(k)+4)$-approximation for any combinatorial auction with single-dimensional signals, with $k$-sized signal space, for SOS and strong-SOS valuations, respectively. All of our results extend to a parameterized version of SOS, $d$-SOS, while losing a factor that depends on $d$.

Includes members:
  Member "interdependent values without single crossing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the buck passing game")
  Member "optimal algorithms for continuous non monotone submodular and dr submodular maximization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "online non monotone dr submodular maximization")
  Member "non monotone continuous dr submodular maximization structure and algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online non monotone dr submodular maximization")
  Member "approximate revenue maximization in interdependent value settings":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust revenue maximization under minimal statistical information")
  Member "optimal mechanisms for selling information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "computing the value of spatio temporal data in wholesale and retail data marketplaces")
  Member "optimal auctions with correlated bidders are easy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "lp based approximation for personalized reserve prices")

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)