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 multivariate generalization of costa s entropy power inequality"
  Abstract: A simple multivariate version of Costa's entropy power inequality is proved. In particular, it is shown that if independent white Gaussian noise is added to an arbitrary multivariate signal, the entropy power of the resulting random variable is a multidimensional concave function of the individual variances of the components of the signal. As a side result, we also give an expression for the Hessian matrix of the entropy and entropy power functions with respect to the variances of the signal components, which is an interesting result in its own right.

Connected through hyperedge HE-1 (induced by source paper "a unifying variational perspective on some fundamental information theoretic inequalities"):
  with members:
    - "gaussian assumption the least favorable but the most useful lecture notes"
    - "an alternative proof of an extremal inequality"
    - "an alternative proof of an extremal entropy inequality"
    - "information theoretic proofs of entropy power inequalities"
    - "an extremal inequality motivated by multiterminal information theoretic problems"

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"
    - "on divergence power inequalities"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "dependence balance based outer bounds for gaussian networks with cooperation and feedback"):
  with members:
    - "interference channels with source cooperation"
    - "interference channels with destination cooperation"
    - "the gaussian mac with conferencing encoders"

Connected through hyperedge HE-4 (induced by source paper "hessian and concavity of mutual information differential entropy and entropy power in linear vector gaussian channels"):
  with members:
    - "information theoretic proofs of entropy power inequalities"
    - "dependence balance based outer bounds for gaussian networks with cooperation and feedback"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "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)