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: "multiuser random coding techniques for mismatched decoding"
  Abstract: This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multipleaccess channel, an error exponent is obtained that is tight with respect to the ensemble average, and positive within the interior of Lapidoth’s achievable rate region. This exponent proves the ensemble tightness of the exponent of Liu and Hughes in the case of maximum-likelihood decoding. An equivalent dual form of Lapidoth’s achievable rate region is given, and the latter is shown to extend immediately to channels with infinite and continuous alphabets. In the setting of single-user mismatched decoding, similar analysis techniques are applied to a refined version of superposition coding, which is shown to achieve rates at least as high as standard superposition coding for any set of randomcoding parameters.

Connected through hyperedge HE-1 (induced by source paper "strategic communication with side information at the decoder"):
  with members:
    - "strong coordination of signals and actions over noisy channels with two sided state information"
    - "persuasion with limited communication capacity"
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "on the role of side information in strategic communication"
    - "persuasion with limited communication"
    - "algorithmic bayesian persuasion"
    - "empirical coordination with two sided state information and correlated source and state"

Connected through hyperedge HE-2 (induced by source paper "converse theorems for the dmc with mismatched decoding"):
  with members:
    - "a general formula for the mismatch capacity"

Connected through hyperedge HE-3 (induced by source paper "mismatched multi letter successive decoding for the multiple access channel"):
  with members:
    - "random coding error exponents for the two user interference channel"
    - "re proving channel polarization theorems an extremality and robustness analysis"
    - "polarization as a novel architecture to boost the classical mismatched capacity of b dmcs"
    - "a technique for deriving one shot achievability results in network information theory"
    - "multiuser coding techniques for mismatched decoding"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "a general formula for the mismatch capacity"
    - "on achievable rates for channels with mismatched decoding"

Connected through hyperedge HE-4 (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 correct decoding exponent of the wiretap channel decoder"
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list random coding error exponents are not universally achievable"
    - "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-5 (induced by source paper "universal decoding for source channel coding with side information"):
  with members:
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list exponents for slepian wolf decoding"
    - "universal decoding for arbitrary channels relative to a given class of decoding metrics"
    - "communication over individual channels a general framework"
    - "the porosity of additive noise sequences"
    - "communication over individual channels"
    - "universal communication part i modulo additive channels"
    - "relations between random coding exponents and the statistical physics of random codes"

Connected through hyperedge HE-6 (induced by source paper "on the reliability function of the discrete memoryless relay channel"):
  with members:
    - "multiuser coding techniques for mismatched decoding"
    - "reliability in source coding with side information"
    - "moderate deviations of lossy source coding for discrete and gaussian sources"
    - "the gelfand pinsker channel strong converse and upper bound for the reliability function"
    - "information spectrum approach to second order coding rate in channel coding"
    - "relations between random coding exponents and the statistical physics of random codes"
    - "capacity and random coding exponents for channel coding with side information"

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)