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: "dynamic rate and channel selection in cognitive radio systems"
  Abstract: In this paper, we investigate dynamic channel and rate selection in cognitive radio systems which exploit a large number of channels free from primary users. In such systems, transmitters may rapidly change the selected (channel, rate) pair to opportunistically learn and track the pair offering the highest throughput. We formulate the problem of sequential channel and rate selection as an online optimization problem, and show its equivalence to a {\it structured} Multi-Armed Bandit problem. The structure stems from inherent properties of the achieved throughput as a function of the selected channel and rate. We derive fundamental performance limits satisfied by {\it any} channel and rate adaptation algorithm, and propose algorithms that achieve (or approach) these limits. In turn, the proposed algorithms optimally exploit the inherent structure of the throughput. We illustrate the efficiency of our algorithms using both test-bed and simulation experiments, in both stationary and non-stationary radio environments. In stationary environments, the packet successful transmission probabilities at the various channel and rate pairs do not evolve over time, whereas in non-stationary environments, they may evolve. In practical scenarios, the proposed algorithms are able to track the best channel and rate quite accurately without the need of any explicit measurement and feedback of the quality of the various channels.

Connected through hyperedge HE-1 (induced by source paper "constrained thompson sampling for wireless link optimization"):
  with members:
    - "beyond the click through rate web link selection with multi level feedback"
    - "efficient beam alignment in millimeter wave systems using contextual bandits"
    - "unimodal thompson sampling for graph structured arms"
    - "bandits with knapsacks"
    - "optimal rate sampling in 802 11 systems"
    - "further optimal regret bounds for thompson sampling"
    - "coding versus arq in fading channels how reliable should the phy be"
    - "multi armed bandits in metric spaces"

Connected through hyperedge HE-2 (induced by source paper "efficient beam alignment in millimeter wave systems using contextual bandits"):
  with members:
    - "agile millimeter wave networks with provable guarantees"
    - "millimeter wave beam selection using out of band spatial information"
    - "energy efficient power and bandwidth allocation in an integrated sub 6 ghz millimeter wave system"
    - "coordinated initial access in millimetre wave standalone networks"
    - "unimodal thompson sampling for graph structured arms"
    - "unimodal bandits regret lower bounds and optimal algorithms"
    - "directional cell discovery in millimeter wave cellular networks"
    - "optimal rate sampling in 802 11 systems"

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)