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: "general auction theoretic strategies for distributed partner selection in cooperative wireless networks"
  Abstract: It is unrealistic to assume that all nodes in an ad hoc wireless network would be willing to participate in cooperative communication, especially if their desired Quality-of- Service (QoS) is achievable via direct transmission. An incentivebased auction mechanism is presented to induce cooperative behavior in wireless networks with emphasis on users with asymmetrical channel fading conditions. A single-object secondprice auction is studied for cooperative partner selection in singlecarrier networks. In addition, a multiple-object bundled auction is analyzed for the selection of multiple simultaneous partners in a cooperative orthogonal frequency-division multiplexing (OFDM) setting. For both cases, we characterize equilibrium outage probability performance, seller revenue, and feedback bounds. The auction-based partner selection allows winning bidders to achieve their desired QoS while compensating the seller who assists them. At the local level sellers aim for revenue maximization, while connections are drawn to min-max fairness at the network level. The proposed strategies for partner selection in self-configuring cooperative wireless networks are shown to be robust under conditions of uncertainty in the number of users requesting cooperation, as well as minimal topology and channel link information available to individual users.

Connected through hyperedge HE-1 (induced by source paper "distributed learning for channel allocation over a shared spectrum"):
  with members:
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "game of thrones fully distributed learning for multi player bandits"
    - "proactive resource management for lte in unlicensed spectrum a deep learning perspective"
    - "deep multi user reinforcement learning for distributed dynamic spectrum access"
    - "game theoretic dynamic channel allocation for frequency selective interference channels"
    - "proactive resource management in lte u systems a deep learning perspective"
    - "propagation path loss models for 5g urban micro and macro cellular scenarios"
    - "multi player bandits a musical chairs approach"

Connected through hyperedge HE-2 (induced by source paper "joint channel selection and power control in infrastructureless wireless networks a multiplayer multiarmed bandit framework"):
  with members:
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"
    - "hedonic coalition formation for distributed task allocation among wireless agents"
    - "adaptive online prediction by following the perturbed leader"

Connected through hyperedge HE-3 (induced by source paper "fully distributed optimal channel assignment for open spectrum access"):
  with members:
    - "max product for maximum weight matching convergence correctness and lp duality"

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.IT(Information Theory)