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: "hybrid coding for gaussian broadcast channels with gaussian sources"
  Abstract: This paper considers a degraded Gaussian broadcast channel over which Gaussian sources are to be communicated. When the sources are independent, this paper shows that hybrid coding achieves the optimal distortion region, the same as that of separate source and channel coding. It also shows that uncoded transmission is not optimal for this setting. For correlated sources, the paper shows that a hybrid coding strategy has a better distortion region than separate source-channel coding below a certain signal to noise ratio threshold. Thus, hybrid coding is a good choice for Gaussian broadcast channels with correlated Gaussian sources.

Connected through hyperedge HE-1 (induced by source paper "distributed source simulation with no communication"):
  with members:
    - "decidability of non interactive simulation of joint distributions"
    - "secure cascade channel synthesis"
    - "on non interactive simulation of joint distributions"
    - "a stronger soft covering lemma and applications"
    - "zero error coordination"
    - "exact common information"
    - "analysis of boolean functions"
    - "simulation of a channel with another channel"

Connected through hyperedge HE-2 (induced by source paper "broadcasting correlated vector gaussians"):
  with members:
    - "a source channel separation theorem with application to the source broadcast problem"
    - "joint unitary triangularization for mimo networks"
    - "hybrid digital analog codes for source channel broadcast of gaussian sources over gaussian channels"
    - "broadcasting correlated gaussians"
    - "vector gaussian multiple description with individual and central receivers"

Connected through hyperedge HE-3 (induced by source paper "hybrid coding an interface for joint source channel coding and network communication"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "on the separation of lossy source network coding and channel coding in wireline networks"
    - "communication to within a fidelity criterion over unknown networks by reduction to reliable communication problems over unknown networks"
    - "optimality and approximate optimality of source channel separation in networks"
    - "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel"
    - "correlated sources over broadcast channels"
    - "wyner ziv coding over broadcast channels digital schemes"
    - "outer bounds on the admissible source region for broadcast channels with dependent sources"

Connected through hyperedge HE-4 (induced by source paper "separate source channel coding for broadcasting correlated gaussians"):
  with members:
    - "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel"
    - "broadcasting correlated gaussians"

Connected through hyperedge HE-5 (induced by source paper "optimality and approximate optimality of source channel separation in networks"):
  with members:
    - "separation of source network coding and channel coding in wireline networks"
    - "on the separation of lossy source network coding and channel coding in wireline networks"
    - "cascade and triangular source coding with side information at the first two nodes"
    - "cascade multiterminal source coding"
    - "approximate characterizations for the gaussian source broadcast distortion region"
    - "multicasting correlated multi source to multi sink over a network"
    - "on multistage successive refinement for wyner ziv source coding with degraded side informations"
    - "coding into a source a direct inverse rate distortion theorem"

Connected through hyperedge HE-6 (induced by source paper "joint source channel coding with correlated interference"):
  with members:
    - "inner and outer bounds for the gaussian cognitive interference channel and new capacity results"
    - "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel"
    - "approximate characterizations for the gaussian source broadcast distortion region"
    - "joint source channel coding with side information using hybrid digital analog codes"
    - "broadcasting correlated gaussians"
    - "superimposed coded and uncoded transmissions of a gaussian source over the gaussian channel"
    - "cognitive radio an information theoretic perspective"

Connected through hyperedge HE-7 (induced by source paper "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel"):
  with members:
    - "broadcasting correlated gaussians"

Connected through hyperedge HE-8 (induced by source paper "broadcasting correlated gaussians"):
  with members:
    - "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel"
    - "sending a bivariate gaussian source over a gaussian mac with feedback"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "sending a bi variate gaussian source over a gaussian mac"

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)