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: "bounds among f divergences"
  Abstract: This paper develops methods to obtain bounds on an $f$-divergence based on one or several other $f$-divergences, dealing with pairs of probability measures defined on arbitrary alphabets. Functional domination is one such approach, where special emphasis is placed on finding the best possible constant upper bounding a ratio of $f$-divergences. Another approach used for the derivation of bounds among $f$-divergences relies on moment inequalities and the logarithmic-convexity property, which is studied in this paper to obtain tight bounds on the relative entropy and Bhattacharyya distance in terms of $\chi^2$ divergences. A rich variety of bounds are shown to hold under boundedness assumptions on the relative information. Special attention is on the total variation distance and its relation to the relative information and relative entropy, including "reverse Pinsker inequalities," as well as on the $E_\gamma$ divergence, which generalizes the total variation distance. Pinsker's inequality is extended for this type of $f$-divergence, a result which leads to an inequality that links the relative entropy and relative information spectrum. Integral expressions of the R\'enyi divergence in terms of the relative information spectrum are derived, leading to bounds on the R\'enyi divergence in terms of either the variational distance or relative entropy.

Connected through hyperedge HE-1 (induced by source paper "empirical and strong coordination via soft covering with polar codes"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "f divergence inequalities"
    - "covert communication over noisy channels a resolvability perspective"
    - "coordination in distributed networks via coded actions with application to power control"
    - "semantic security capacity for wiretap channels of type ii"
    - "strong coordination over multi hop line networks"
    - "empirical coordination for joint source channel coding"
    - "joint empirical coordination of source and channel"

Connected through hyperedge HE-2 (induced by source paper "information recovery from pairwise measurements"):
  with members:
    - "community recovery in graphs with locality"
    - "stochastic block model and community detection in the sparse graphs a spectral algorithm with optimal rate of recovery"
    - "information recovery from pairwise measurements a shannon theoretic approach"
    - "semidefinite programs on sparse random graphs and their application to community detection"
    - "discrete signal processing on graphs sampling theory"
    - "optimal haplotype assembly from high throughput mate pair reads"
    - "near optimal joint object matching via convex relaxation"
    - "accurate community detection in the stochastic block model via spectral algorithms"

Connected through hyperedge HE-3 (induced by source paper "e_ gamma resolvability"):
  with members:
    - "f divergence inequalities"
    - "the likelihood encoder for lossy compression"
    - "soft covering with high probability"
    - "semantic security capacity for wiretap channels of type ii"
    - "one shot mutual covering lemma and marton s inner bound with a common message"
    - "resolvability in e γ with applications to lossy compression and wiretap channels"
    - "robustness of sparse recovery via f minimization a topological viewpoint"
    - "strong converse and second order asymptotics of channel resolvability"

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"
    - "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"
    - "r enyi divergence and majorization"

Connected through hyperedge HE-5 (induced by source paper "upper bounds on the relative entropy and r enyi divergence as a function of total variation distance for finite alphabets"):
  with members:
    - "optimal quantization for distribution synthesis"
    - "on the r e nyi divergence and the joint range of relative entropies"
    - "channels with cost constraints strong converse and dispersion"
    - "renyi divergence and kullback leibler divergence"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"
    - "entropy bounds for discrete random variables via maximal coupling"
    - "on pinsker s and vajda s type inequalities for csiszar s f divergences"

Connected through hyperedge HE-6 (induced by source paper "strong data processing inequalities and phi sobolev inequalities for discrete channels"):
  with members:
    - "strong data processing inequalities for channels and bayesian networks"
    - "bounds between contraction coefficients"
    - "dissipation of information in channels with input constraints"
    - "key capacity with limited one way communication for product sources"
    - "tractable inference for complex stochastic processes"
    - "outer bounds for multiterminal source coding via a strong data processing inequality"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"

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)