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: "on divergence power inequalities"
  Abstract: Expressions for (entropy-power inequality (EPI) Shannon type) divergence-power inequalities (DPIs) in two cases (time-discrete and time-continuous) of stationary random processes are given. The new expressions connect the divergence rate of the sum of independent processes, the individual divergence rate of each process, and their power spectral densities. All divergences are between a process and a Gaussian process with same second-order statistics, and are assumed to be finite. A new proof of the Shannon EPI, based on the relationship between divergence and causal minimum mean-square error (CMMSE) in Gaussian channels with large signal-to-noise ratio, is also shown

Connected through hyperedge HE-1 (induced by source paper "yet another proof of the entropy power inequality"):
  with members:
    - "optimal transportation to the entropy power inequality"
    - "beyond the entropy power inequality via rearrangements"
    - "information theoretic proofs of entropy power inequalities"
    - "a simple proof of the entropy power inequality via properties of mutual information"
    - "generalized entropy power inequalities and monotonicity properties of information"

Connected through hyperedge HE-2 (induced by source paper "information theoretic proofs of entropy power inequalities"):
  with members:
    - "hessian and concavity of mutual information differential entropy and entropy power in linear vector gaussian channels"
    - "concavity of entropy under thinning"
    - "a multivariate generalization of costa s entropy power inequality"
    - "mixing and non mixing local minima of the entropy contrast for blind source separation"
    - "the gaussian multiple access wire tap channel with collective secrecy constraints"
    - "generalized entropy power inequalities and monotonicity properties of information"
    - "an extremal inequality motivated by multiterminal information theoretic problems"
    - "the gaussian multiple access wire tap channel"

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)