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 perspectives on brascamp lieb inequality and its reverse"):
  Abstract: We introduce an inequality which may be viewed as a generalization of both the Brascamp-Lieb inequality and its reverse (Barthe's inequality), and prove its information-theoretic (i.e.\ entropic) formulation. This result leads to a unified approach to functional inequalities such as the variational formula of Renyi entropy, hypercontractivity and its reverse, strong data processing inequalities, and transportation-cost inequalities, whose utility in the proofs of various coding theorems has gained growing popularity recently. We show that our information-theoretic setting is convenient for proving properties such as data processing, tensorization, convexity (Riesz-Thorin interpolation) and Gaussian optimality. In particular, we elaborate on a "doubling trick" used by Lieb and Geng-Nair to prove several results on Gaussian optimality. Several applications are discussed, including a generalization of the Brascamp-Lieb inequality involving Gaussian random transformations, the determination of Wyner's common information of vector Gaussian sources, and the achievable rate region of certain key generation problems in the case of vector Gaussian sources.

Includes members:
  Member "arimoto r enyi conditional entropy and bayesian m ary hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "generalizing bottleneck problems")
  Member "strengthening the entropy power inequality":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an entropy inequality for symmetric random variables")
  Member "algorithmic and optimization aspects of brascamp lieb inequalities via operator scaling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rigorous guarantees for tyler s m estimator via quantum expansion")
  Member "brascamp lieb inequality and its reverse an information theoretic view":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dispersion bound for the wyner ahlswede k orner network via reverse hypercontractivity on types")
  Member "converses for distributed estimation via strong data processing inequalities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "strong data processing inequalities for channels and bayesian networks")
  Member "secret key generation with one communicator and a one shot converse via hypercontractivity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "communication for generating correlation a unifying survey")
  Member "on non interactive simulation of joint distributions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "communication for generating correlation a unifying survey")
  Member "a note on the strong data processing inequalities in bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "comparison of channels criteria for domination by a symmetric channel")

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)