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: "mixture based modeling of correlated interference in a poisson field of interferers"
  Abstract: Interference in PPP-based wireless networks exhibit spatial correlation. Because of which, any joint analysis, involving interferences at multiple points, either end up with expressions requiring numerical integration over $\mathbb{R}^2$, or become analytically too difficult to undertake. To tackle this issue, the paper presents an alternate approach, to such analysis, in the form a tractable method for modeling correlated PPP interference; which, at its core, employs a correlation framework constructed using the concept of \textit{mixtures of random variables}. A secondary framework based on the more standard method of linear combinations of random variables is also presented, mainly for comparison purpose. To study the performance of the proposed model, joint distribution of SIRs at $N$ spatial points is derived in the form of joint CCDF. The expressions are in closed-form, involving finite sums and products, that match well with the exact PPP-based results. The tightness of the results, however, depends on the values of $\lambda p$ (interferer intensity) and $\alpha$ (path loss exponent).

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)