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 "approximation algorithms for secondary spectrum auctions"):
  Abstract: We study combinatorial auctions for the secondary spectrum market. In this market, short-term licenses shall be given to wireless nodes for communication in their local neighborhood. In contrast to the primary market, channels can be assigned to multiple bidders, provided that the corresponding devices are well separated such that the interference is sufficiently low. Interference conflicts are described in terms of a conflict graph in which the nodes represent the bidders and the edges represent conflicts such that the feasible allocations for a channel correspond to the independent sets in the conflict graph. #R##N#In this paper, we suggest a novel LP formulation for combinatorial auctions with conflict graph using a non-standard graph parameter, the so-called inductive independence number. Taking into account this parameter enables us to bypass the well-known lower bound of \Omega(n^{1-\epsilon}) on the approximability of independent set in general graphs with n nodes (bidders). We achieve significantly better approximation results by showing that interference constraints for wireless networks yield conflict graphs with bounded inductive independence number. #R##N#Our framework covers various established models of wireless communication, e.g., the protocol or the physical model. For the protocol model, we achieve an O(\sqrt{k})-approximation, where k is the number of available channels. For the more realistic physical model, we achieve an O(\sqrt{k} \log^2 n) approximation based on edge-weighted conflict graphs. Combining our approach with the the LP-based framework of Lavi and Swamy, we obtain incentive compatible mechanisms for general bidders with arbitrary valuations on bundles of channels specified in terms of demand oracles.

Includes members:
  Member "approximation algorithms for wireless link scheduling with flexible data rates":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "wireless link capacity under shadowing and fading")
  Member "the power of non uniform wireless power":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data dissemination in unified dynamic wireless networks")
  Member "secondary spectrum auctions for symmetric and submodular bidders":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "effective wireless scheduling via hypergraph sketches")
  Member "wireless capacity with oblivious power in general metrics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "reception capacity definitions game theory and hardness")
  Member "a constant factor approximation for wireless capacity maximization with power control in the sinr model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reception capacity definitions game theory and hardness")
  Member "wireless scheduling with power control":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "effective wireless scheduling via hypergraph sketches")
  Member "bundling equilibrium in combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "truthfulness with value maximizing bidders")
  Member "opportunity cost algorithms for combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "effective wireless scheduling via hypergraph sketches")

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.DS(Data Structures and Algorithms)