human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "information theoretic proofs of entropy power inequalities"):
  Abstract: While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, up to now Shannon's entropy power inequality (EPI) is an exception: Existing information theoretic proofs of the EPI hinge on representations of differential entropy using either Fisher information or minimum mean-square error (MMSE), which are derived from de Bruijn's identity. In this paper, we first present an unified view of these proofs, showing that they share two essential ingredients: 1) a data processing argument applied to a covariance-preserving linear transformation; 2) an integration over a path of a continuous Gaussian perturbation. Using these ingredients, we develop a new and brief proof of the EPI through a mutual information inequality, which replaces Stam and Blachman's Fisher information inequality (FII) and an inequality for MMSE by Guo, Shamai, and Verdu used in earlier proofs. The result has the advantage of being very simple in that it relies only on the basic properties of mutual information. These ideas are then generalized to various extended versions of the EPI: Zamir and Feder's generalized EPI for linear transformations of the random variables, Takano and Johnson's EPI for dependent variables, Liu and Viswanath's covariance-constrained EPI, and Costa's concavity inequality for the entropy power.

Includes members:
  Member "hessian and concavity of mutual information differential entropy and entropy power in linear vector gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the geometry of community detection via the mmse matrix")
  Member "concavity of entropy under thinning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "thinning photonic beamsplitting and a general discrete entropy power inequality")
  Member "a multivariate generalization of costa s entropy power inequality":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a unifying variational perspective on some fundamental information theoretic inequalities")
  Member "on divergence power inequalities":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "yet another proof of the entropy power inequality")
  Member "mixing and non mixing local minima of the entropy contrast for blind source separation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "uniqueness analysis of non unitary matrix joint diagonalization")
  Member "the gaussian multiple access wire tap channel with collective secrecy constraints":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the secrecy capacity of the broadcast wiretap channel with limited csi feedback")
  Member "generalized entropy power inequalities and monotonicity properties of information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "two remarks on generalized entropy power inequalities")
  Member "an extremal inequality motivated by multiterminal information theoretic problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vector gaussian successive refinement with degraded side information")

Question: Please tell me which class the source paper 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)