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 note on a characterization of renyi measures and its relation to composite hypothesis testing"
  Abstract: The R\'enyi information measures are characterized in terms of their Shannon counterparts, and properties of the former are recovered from first principle via the associated properties of the latter. Motivated by this characterization, a two-sensor composite hypothesis testing problem is presented, and the optimal worst case miss-detection exponent is obtained in terms of a R\'enyi divergence.

Connected through hyperedge HE-1 (induced by source paper "the augustin capacity and center"):
  with members:
    - "the renyi capacity and center"
    - "the sphere packing bound for memoryless channels"
    - "the augustin center and the sphere packing bound for memoryless channels"
    - "exponent function for stationary memoryless channels with input cost at rates above the capacity"
    - "the sphere packing bound via augustin s method"
    - "channels with cost constraints strong converse and dispersion"
    - "constant compositions in the sphere packing bound for classical quantum channels"
    - "renyi divergence and kullback leibler divergence"

Connected through hyperedge HE-2 (induced by source paper "a variational characterization of r enyi divergences"):
  with members:
    - "brascamp lieb inequality and its reverse an information theoretic view"
    - "on the renyi divergence joint range of relative entropies and a channel coding theorem"

Connected through hyperedge HE-3 (induced by source paper "analysis of remaining uncertainties and exponents under various conditional r e nyi entropies"):
  with members:
    - "uniform random number generation from markov chains non asymptotic and asymptotic analyses"
    - "security analysis of varepsilon almost dual universal 2 hash functions smoothing of min entropy versus smoothing of renyi entropy of order 2"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "equivocations exponents and second order coding rates under various r enyi information measures"
    - "asymmetric evaluations of erasure and undetected error probabilities"
    - "list decoding random coding exponents and expurgated exponents"
    - "encoding tasks and renyi entropy"
    - "secure multiterminal source coding with side information at the eavesdropper"

Connected through hyperedge HE-4 (induced by source paper "on the renyi divergence joint range of relative entropies and a channel coding theorem"):
  with members:
    - "strong converse theorems for classes of multimessage multicast networks a renyi divergence approach"
    - "bounds among f divergences"
    - "upper bounds on the relative entropy and r enyi divergence as a function of total variation distance for finite alphabets"
    - "tight bounds for symmetric divergence measures and a refined bound for lossless source coding"
    - "information theoretic applications of the logarithmic probability comparison bound"
    - "renyi divergence and kullback leibler divergence"
    - "multiple source adaptation and the renyi divergence"
    - "on pinsker s and vajda s type inequalities for csiszar s f divergences"

Connected through hyperedge HE-5 (induced by source paper "on the r e nyi divergence and the joint range of relative entropies"):
  with members:
    - "tight bounds for symmetric divergence measures and a refined bound for lossless source coding"
    - "information theoretic applications of the logarithmic probability comparison bound"
    - "minimization problems based on a parametric family of relative entropies ii reverse projection"
    - "on pairs of f divergences and their joint range"
    - "guessing under source uncertainty"
    - "tightened upper bounds on the ml decoding error probability of binary linear block codes"

Connected through hyperedge HE-6 (induced by source paper "encoding tasks and renyi entropy"):
  with members:
    - "distributed storage for data security"
    - "guessing revisited a large deviations approach"
    - "guessing under source uncertainty"

Connected through hyperedge HE-7 (induced by source paper "renyi divergence and kullback leibler divergence"):
  with members:
    - "multiple source adaptation and the renyi divergence"
    - "on pinsker s and vajda s type inequalities for csiszar s f divergences"
    - "r enyi divergence and majorization"

Connected through hyperedge HE-8 (induced by source paper "delay and redundancy in lossless source coding"):
  with members:
    - "bounded expected delay in arithmetic coding"

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)