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 "variable length resolvability for general sources and channels"):
  Abstract: We introduce the problem of variable-length source resolvability, where a given target probability distribution is approximated by encoding a variable-length uniform random number, and the asymptotically minimum average length rate of the uniform random numbers, called the (variable-length) resolvability, is investigated. We first analyze the variable-length resolvability with the variational distance as an approximation measure. Next, we investigate the case under the divergence as an approximation measure. When the asymptotically exact approximation is required, it is shown that the resolvability under the two kinds of approximation measures coincides. We then extend the analysis to the case of channel resolvability, where the target distribution is the output distribution via a general channel due to the fixed general source as an input. The obtained characterization of the channel resolvability is fully general in the sense that when the channel is just the identity mapping, the characterization reduces to the general formula for the source resolvability. We also analyze the second-order variable-length resolvability.

Includes members:
  Member "variable length coding with cost allowing non vanishing error probability":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimum overflow thresholds in variable length source coding allowing non vanishing error probability")
  Member "strong converse and second order asymptotics of channel resolvability":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication for generating correlation a unifying survey")
  Member "an information spectrum approach to weak variable length source coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "variable length source dispersions differ under maximum and average error criteria")
  Member "variable length compression allowing errors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "asymptotic expansions of smooth r e nyi entropies and their applications")
  Member "second order resolvability intrinsic randomness and fixed length source coding for mixed sources information spectrum approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "interval algorithm for random number generation information spectrum approach")

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)