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: "universal and composite hypothesis testing via mismatched divergence"
  Abstract: For the universal hypothesis testing problem, where the goal is to decide between the known null hypothesis distribution and some other unknown distribution, Hoeffding proposed a universal test in the nineteen sixties. Hoeffding's universal test statistic can be written in terms of Kullback-Leibler (K-L) divergence between the empirical distribution of the observations and the null hypothesis distribution. In this paper a modification of Hoeffding's test is considered based on a relaxation of the K-L divergence, referred to as the mismatched divergence. The resulting mismatched test is shown to be a generalized likelihood-ratio test (GLRT) for the case where the alternate distribution lies in a parametric family of distributions characterized by a finite-dimensional parameter, i.e., it is a solution to the corresponding composite hypothesis testing problem. For certain choices of the alternate distribution, it is shown that both the Hoeffding test and the mismatched test have the same asymptotic performance in terms of error exponents. A consequence of this result is that the GLRT is optimal in differentiating a particular distribution from others in an exponential family. It is also shown that the mismatched test has a significant advantage over the Hoeffding test in terms of finite sample size performance for applications involving large alphabet distributions. This advantage is due to the difference in the asymptotic variances of the two test statistics under the null hypothesis.

Connected through hyperedge HE-1 (induced by source paper "error exponents of mismatched likelihood ratio testing"):
  with members:
    - "universal outlier hypothesis testing"
    - "robust hypothesis testing with a relative entropy tolerance"

Connected through hyperedge HE-2 (induced by source paper "asymptotically optimal one and two sample testing with kernels"):
  with members:
    - "robust kullback leibler divergence and universal hypothesis testing for continuous distributions"
    - "mmd gan towards deeper understanding of moment matching network"
    - "m statistic for kernel change point detection"
    - "nonparametric detection of anomalous data streams"
    - "renyi divergence and kullback leibler divergence"
    - "universal outlier hypothesis testing"

Connected through hyperedge HE-3 (induced by source paper "operational interpretation of renyi information measures via composite hypothesis testing against product and markov distributions"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "two measures of dependence"
    - "uniform random number generation from markov chains non asymptotic and asymptotic analyses"
    - "equivocations exponents and second order coding rates under various r enyi information measures"
    - "universal channel coding for exponential family of channels"
    - "universal channel coding for general output alphabet"
    - "converses for secret key agreement and secure computing"
    - "encoding tasks and renyi entropy"

Connected through hyperedge HE-4 (induced by source paper "signal amplitude estimation and detection from unlabeled binary quantized samples"):
  with members:
    - "signal recovery from unlabeled samples"
    - "unlabeled sensing with random linear measurements"

Connected through hyperedge HE-5 (induced by source paper "statistical anomaly detection via composite hypothesis testing for markov models"):
  with members:
    - "an improved composite hypothesis test for markov models with applications in network anomaly detection"

Connected through hyperedge HE-6 (induced by source paper "passive dynamics in mean field control"):
  with members:
    - "electrical vehicles in the smart grid a mean field game analysis"
    - "mean field for markov decision processes from discrete to continuous optimization"

Connected through hyperedge HE-7 (induced by source paper "sequentiality and adaptivity gains in active hypothesis testing"):
  with members:
    - "active sequential hypothesis testing"
    - "controlled sensing for multihypothesis testing"
    - "non adaptive probabilistic group testing with noisy measurements near optimal bounds with efficient algorithms"
    - "active classification theory and application to underwater inspection"
    - "robust hypothesis testing with a relative entropy tolerance"

Connected through hyperedge HE-8 (induced by source paper "objective information theory a sextuple model and 9 kinds of metrics"):
  with members:
    - "conditional entropy based user selection for multiuser mimo systems"
    - "mutual information of iid complex gaussian signals on block rayleigh faded channels"
    - "information inequalities for joint distributions with interpretations and applications"

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)