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: "a simple proof of the entropy power inequality via properties of mutual information"
  Abstract: While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, Shannon's entropy power inequality (EPI) seems to be an exception: available information theoretic proofs of the EPI hinge on integral representations of differential entropy using either Fisher's information (FI) or minimum mean-square error (MMSE). In this paper, we first present a unified view of proofs via FI and MMSE, showing that they are essentially dual versions of the same proof, and then fill the gap by providing a new, simple proof of the EPI, which is solely based on the properties of mutual information and sidesteps both FI or MMSE representations.

Connected through hyperedge HE-1 (induced by source paper "optimal transportation to the entropy power inequality"):
  with members:
    - "at every corner determining corner points of two user gaussian interference channels"
    - "links between the logarithmic sobolev inequality and the convolution inequalities for entropy and fisher information"
    - "yet another proof of the entropy power inequality"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "beyond the entropy power inequality via rearrangements"
    - "information theoretic proofs of entropy power inequalities"
    - "generalized entropy power inequalities and monotonicity properties of information"

Connected through hyperedge HE-2 (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"
    - "on divergence power inequalities"
    - "generalized entropy power inequalities and monotonicity properties of information"

Connected through hyperedge HE-3 (induced by source paper "a strengthened entropy power inequality for log concave densities"):
  with members:
    - "beyond the entropy power inequality via rearrangements"
    - "the concavity of renyi entropy power"
    - "an information theoretic proof of nash s inequality"
    - "generalized entropy power inequalities and monotonicity properties of information"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-4 (induced by source paper "continuity of mutual entropy in the large signal to noise ratio limit"):
  with members:
    - "monotonicity thinning and discrete versions of the entropy power inequality"
    - "mutual information and minimum mean square error in gaussian channels"

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)