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 "two measures of dependence"):
  Abstract: Two families of dependence measures between random variables are introduced. They are based on the R\'enyi divergence of order $\alpha$ and the relative $\alpha$-entropy, respectively, and both dependence measures reduce to Shannon's mutual information when their order $\alpha$ is one. The first measure shares many properties with the mutual information, including the data-processing inequality, and can be related to the optimal error exponents in composite hypothesis testing. The second measure does not satisfy the data-processing inequality, but appears naturally in the context of distributed task encoding.

Includes members:
  Member "operational interpretation of renyi information measures via composite hypothesis testing against product and markov distributions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the renyi capacity and center")
  Member "distributed task encoding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tight bounds on the r enyi entropy via majorization with applications to guessing and compression")
  Member "dependence measures bounding the exploration bias for general measurements":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "novel change of measure inequalities and pac bayesian bounds")
  Member "f divergence inequalities":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on implicit regularization in beta vaes")
  Member "minimization problems based on relative alpha entropy ii reverse projection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generalized bayesian cramer rao inequality via information geometry of relative alpha entropy")
  Member "encoding tasks and renyi entropy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "asymptotic expansions of smooth r e nyi entropies and their applications")
  Member "minimization problems based on relative alpha entropy i forward projection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generalized bayesian cramer rao inequality via information geometry of relative alpha entropy")
  Member "renyi divergence and kullback leibler divergence":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "review analyze and design a comprehensive deep reinforcement learning framework")

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)