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: "r enyi resolvability and its applications to the wiretap channel"
  Abstract: The conventional channel resolvability problem refers to the determination of the minimum rate needed for an input process to approximate the output distribution of a channel in either the total variation distance or the relative entropy. In contrast to previous works, in this paper, we use the (normalized or unnormalized) R\'enyi divergence (with the R\'enyi parameter in [0,2]) to measure the level of approximation. We also provide asymptotic expressions for normalized R\'enyi divergence when the R\'enyi parameter is larger than or equal to $1$ as well as (lower and upper) bounds for the case when the same parameter is smaller than $1$. We characterize the minimum rate needed to ensure that the R\'enyi resolvability vanishes asymptotically. The optimal rates are the same for both the normalized and unnormalized cases. In addition, the minimum rate when the R\'enyi parameter no larger than $1$ equals the minimum mutual information over all input distributions that induce the target output distribution similarly to the traditional case. When the R\'enyi parameter is larger than $1$ the minimum rate is, in general, larger than the mutual information. The optimal R\'enyi resolvability is proven to vanish at least exponentially fast for both of these two cases, as long as the code rate is larger than the minimum admissible one. The optimal exponential rate of decay for i.i.d. random codes is also characterized exactly. We apply these results to the wiretap channel, and completely characterize the optimal tradeoff between the rates of the secret and non-secret messages when the leakage measure is given by the (unnormalized) R\'enyi divergence. This tradeoff differs from the conventional setting when the leakage is measured by the traditional mutual information.

Connected through hyperedge HE-1 (induced by source paper "a correlation measure based on vector valued l_p norms"):
  with members:
    - "exact exponent for soft covering"
    - "exact soft covering exponent"
    - "generalizing bottleneck problems"
    - "measuring secrecy by the probability of a successful guess"
    - "exact random coding secrecy exponents for the wiretap channel"
    - "a large deviations approach to secure lossy compression"
    - "f divergence inequalities"
    - "semantic security capacity for wiretap channels of type ii"

Connected through hyperedge HE-2 (induced by source paper "resolvability on continuous alphabets"):
  with members:
    - "channel resolvability theorems for general sources and channels"
    - "mac resolvability first and second order results"
    - "the mac resolvability region semantic security and its operational implications"
    - "soft covering with high probability"
    - "strong converse and second order asymptotics of channel resolvability"
    - "renyi divergence and kullback leibler divergence"
    - "informational divergence approximations to product distributions"
    - "strong secrecy from channel resolvability"

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)