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 "comparison of channels criteria for domination by a symmetric channel"):
  Abstract: This paper studies the basic question of whether a given channel    $V$    can be dominated (in the precise sense of being more noisy) by a    $q$   -ary symmetric channel. The concept of less noisy relation between channels originated in network information theory (broadcast channels) and is defined in terms of mutual information or Kullback–Leibler divergence. We provide an equivalent characterization in terms of    $\chi ^{2}$   -divergence. Furthermore, we develop a simple criterion for domination by a    $q$   -ary symmetric channel in terms of the minimum entry of the stochastic matrix defining the channel    $V$   . The criterion is strengthened for the special case of additive noise channels over finite Abelian groups. Finally, it is shown that domination by a symmetric channel implies (via comparison of Dirichlet forms) a logarithmic Sobolev inequality for the original channel.

Includes members:
  Member "strong data processing inequalities for channels and bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")
  Member "bounds between contraction coefficients":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on universal features for high dimensional learning and inference")
  Member "a note on the strong data processing inequalities in bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "application of information percolation method to reconstruction problems on graphs")
  Member "dissipation of information in channels with input constraints":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "broadcasting on random directed acyclic graphs")
  Member "universal polar codes for more capable and less noisy channels and sources":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "universal polarization for processes with memory")
  Member "strong data processing inequalities and phi sobolev inequalities for discrete channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on data processing and majorization inequalities for f divergences with applications")
  Member "capacity regions of two new classes of 2 receiver broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "superposition coding is almost always optimal for the poisson broadcast 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)