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: "exact correct decoding exponent of the wiretap channel decoder"
  Abstract: The performance of the achievability scheme for Wyner's wiretap channel model is examined from the perspective of the probability of correct decoding, Pc, at the wiretap channel decoder. In particular, for finite-alphabet memoryless channels, the exact random coding exponent of Pc is derived as a function of the total coding rate R1 and the rate of each subcode R2. Two different representations are given for this function and its basic properties are provided. We also characterize the region of pairs of rates (R1, R2) of full security in the sense of the random coding exponent of Pc, in other words, the region where the exponent of this achievability scheme is the same as that of blind guessing at the eavesdropper side. Finally, an analogous derivation of the correct-decoding exponent is outlined for the case of the Gaussian channel.

Connected through hyperedge HE-1 (induced by source paper "random coding error exponents for the two user interference channel"):
  with members:
    - "mismatched multi letter successive decoding for the multiple access channel"
    - "optimal achievable rates for interference networks with random codes"
    - "list decoding random coding exponents and expurgated exponents"
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list random coding error exponents are not universally achievable"
    - "multiuser random coding techniques for mismatched decoding"
    - "the generalized random energy model and its application to the statistical physics of ensembles of hierarchical codes"
    - "interference channel capacity region for randomized fixed composition codes"

Connected through hyperedge HE-2 (induced by source paper "exact random coding error exponents of optimal bin index decoding"):
  with members:
    - "error exponents for broadcast channels with degraded message sets"

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)