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: "channel coding and lossy source coding using a generator of constrained random numbers"
  Abstract: Stochastic encoders for channel coding and lossy source coding are introduced with a rate close to the fundamental limits, where the only restriction is that the channel input alphabet and the reproduction alphabet of the lossy source code are finite. Random numbers, which satisfy a condition specified by a function and its value, are used to construct stochastic encoders. The proof of the theorems is based on the hash property of an ensemble of functions, where the results are extended to general channels/sources and alternative formulas are introduced for channel capacity and the rate-distortion region. Since an ensemble of sparse matrices has a hash property, we can construct a code by using sparse matrices.

Connected through hyperedge HE-1 (induced by source paper "communication for generating correlation a unifying survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact exponent for soft covering"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"
    - "strong functional representation lemma and applications to coding theorems"

Connected through hyperedge HE-2 (induced by source paper "communication for generating correlation a survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact soft covering exponent"
    - "on exact and infty r enyi common informations"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"

Connected through hyperedge HE-3 (induced by source paper "successive cancellation decoding of linear source code"):
  with members:
    - "on the error probability of stochastic decision and stochastic decoding"

Connected through hyperedge HE-4 (induced by source paper "multi terminal codes using constrained random number generators"):
  with members:
    - "on the error probability of stochastic decision and stochastic decoding"
    - "construction of a channel code from an arbitrary source code with decoder side information"
    - "construction of slepian wolf source code and broadcast channel code based on hash property"

Connected through hyperedge HE-5 (induced by source paper "on the error probability of stochastic decision and stochastic decoding"):
  with members:
    - "construction of a channel code from an arbitrary source code with decoder side information"

Connected through hyperedge HE-6 (induced by source paper "construction of a channel code from an arbitrary source code with decoder side information"):
  with members:
    - "on the error probability of stochastic decision and stochastic decoding"
    - "achievability proof via output statistics of random binning"
    - "construction of slepian wolf source code and broadcast channel code based on hash property"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "performance of polar codes for channel and source coding"

Connected through hyperedge HE-7 (induced by source paper "information complexity density and simulation of protocols"):
  with members:
    - "interactive communication for data exchange"
    - "converses for secret key agreement and secure computing"
    - "secret key agreement general capacity and second order asymptotics"
    - "achievability proof via output statistics of random binning"
    - "channel simulation via interactive communications"
    - "information equals amortized communication"
    - "information spectrum approach to second order coding rate in channel coding"
    - "information inequalities for joint distributions with interpretations and applications"

Connected through hyperedge HE-8 (induced by source paper "how to achieve the capacity of asymmetric channels"):
  with members:
    - "on the scaling exponent of polar codes for binary input energy harvesting channels"
    - "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel"
    - "construction of polar codes with sublinear complexity"
    - "polar codes for broadcast channels"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "finite length scaling for polar codes"
    - "achieving marton s region for broadcast channels using polar codes"

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)