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: "capacity of random channels with large alphabets"
  Abstract: We consider discrete memoryless channels with input alphabet size   \begin{document}  $n$ \end{document}   and output alphabet size   \begin{document}  $m$ \end{document}  , where   \begin{document}  $m=\left\lceil{γ n}\right\rceil$ \end{document}   for some constant   \begin{document}  $γ>0$ \end{document}  . The channel transition matrix consists of entries that, before being normalized, are independent and identically distributed nonnegative random variables   \begin{document}  $V$ \end{document}   and such that   \begin{document}  $\mathbb{E}{(V \log V)^2}  . We prove that in the limit as   \begin{document}  $n{\to }∞$ \end{document}   the capacity of such a channel converges to   \begin{document}  $\text{Ent}(V) / \mathbb{E}[V]$ \end{document}   almost surely and in   \begin{document}  $\text{L}^{2}$ \end{document}  , where   \begin{document}  $\text{Ent}(V):= \mathbb{E}[{V\log V}]-\mathbb{E}[{V}]\log \mathbb{E}[{V}]$ \end{document}   denotes the entropy of   \begin{document}  $V$ \end{document}  . We further show that, under slightly different model assumptions, the capacity of these random channels converges to this asymptotic value exponentially in   \begin{document}  $n$ \end{document}  . Finally, we present an application in the context of Bayesian optimal experiment design.

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)