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: "local large deviations mcmillian theorem for multitype galton watson processes"
  Abstract: In this article we prove a local large deviation principle (LLDP) for the critical multitype Galton-Watson process from spectral potential point. We define the so-called spectral potential $U_{\mathbb{Q}}(\,\cdot,\,\pi)$ for the Galton-Watson process, where $\pi$ is normalized eigen vector corresponding to the leading eigen value $1$ of the transition matrix $A(\cdot,\,\cdot)$ defined from ${\mathbb{Q}},$ the transition kernel. We show that the Kullback action or the deviation function, $J(\pi,\nu),$ with respect to an empirical offspring measure, $\nu,$ is the Legengre dual of $U_{\mathbb{Q}}(\,\cdot,\,\pi).$ From the LLDP we deduce a full large deviation principle and a weak variant of the classical McMillian Theorem for the multitype Galton-Watson process. To be specific, given any empirical offspring measure $\varpi,$ we show the number of critical multitype Galton-Watson processes on $n$ vertices is approximately $e^{n\langle H_{\varpi},\,\pi\rangle},$ where $H_{\varpi}$ is suitably defined entropy.

Connected through hyperedge HE-1 (induced by source paper "local large deviation principle large deviation principle and information theory for the signal to interference and noise ratio graph models"):
  with members:
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"
    - "interference modeling in cognitive radio networks a survey"
    - "lossy asymptotic equipartition property for geometric networked data structures"
    - "sinr model with best server association for high availability studies of wireless networks"

Connected through hyperedge HE-2 (induced by source paper "local large deviation principle large deviation principle for the signal to interference and noise ratio graph models"):
  with members:
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"

Connected through hyperedge HE-3 (induced by source paper "local large deviations a mcmillian theorem for typed random graph processes"):
  with members:
    - "lossy asymptotic equipartition property for networked data structures"
    - "lossy asymptotic equipartition property for hierarchical data structures"

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)