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: "sending a bi variate gaussian source over a gaussian mac"
  Abstract: We consider a problem where a memoryless bi-variate Gaussian source is to be transmitted over an additive white Gaussian multiple-access channel with two transmitting terminals and one receiving terminal. The first transmitter only sees the first source component and the second transmitter only sees the second source component. We are interested in the pair of mean squared-error distortions at which the receiving terminal can reproduce each of the source components. It is demonstrated that in the symmetric case, below a certain signal-to-noise ratio (SNR) threshold, which is determined by the source correlation, uncoded communication is optimal. For SNRs above this threshold we present outer and inner bounds on the achievable distortions

Connected through hyperedge HE-1 (induced by source paper "on the energy distortion tradeoff of gaussian broadcast channels with feedback"):
  with members:
    - "on the ozarow leung scheme for the gaussian broadcast channel with feedback"
    - "interactive schemes for the awgn channel with noisy feedback"
    - "insufficiency of linear feedback schemes in gaussian broadcast channels with common message"
    - "mimo mac bc duality with linear feedback coding schemes"
    - "source channel coding theorems for the multiple access relay channel"
    - "lqg control approach to gaussian broadcast channels with feedback"
    - "optimality and approximate optimality of source channel separation in networks"
    - "variations on a theme by schalkwijk and kailath"

Connected through hyperedge HE-2 (induced by source paper "distortion bounds and two way protocols for one shot transmission of correlated random variables"):
  with members:
    - "sending a bivariate gaussian source over a gaussian mac with feedback"
    - "sending a bi variate gaussian source over a gaussian mac"

Connected through hyperedge HE-3 (induced by source paper "a new data processing inequality and its applications in distributed source and channel coding"):
  with members:
    - "sending a bi variate gaussian source over a gaussian mac"
    - "an outer bound for the multi terminal rate distortion region"
    - "an infeasibility result for the multiterminal source coding problem"
    - "a single letter upper bound for the sum rate of multiple access channels with correlated sources"

Connected through hyperedge HE-4 (induced by source paper "distributed joint source channel coding for functions over a multiple access channel"):
  with members:
    - "distributed joint source channel coding on a multiple access channel with side information"
    - "communicating the difference of correlated gaussian sources over a mac"
    - "lattices for distributed source coding jointly gaussian sources and reconstruction of a linear function"
    - "sending a bi variate gaussian source over a gaussian mac"

Connected through hyperedge HE-5 (induced by source paper "joint source channel coding over a fading multiple access channel with partial channel state information"):
  with members:
    - "distributed joint source channel coding on a multiple access channel with side information"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-6 (induced by source paper "sending a bivariate gaussian source over a gaussian mac with feedback"):
  with members:
    - "on the gaussian mac with imperfect feedback"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-7 (induced by source paper "on optimal distributed joint source channel coding for correlated gaussian sources over gaussian channels"):
  with members:
    - "distributed joint source channel coding on a multiple access channel with side information"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-8 (induced by source paper "distributed joint source channel coding on a multiple access channel with side information"):
  with members:
    - "sending a bivariate gaussian source over a gaussian mac with feedback"
    - "lattice quantization with side information codes asymptotics and applications in sensor networks"
    - "sending a bi variate gaussian source over a gaussian mac"
    - "coding for the feedback gel fand pinsker channel and the feedforward wyner ziv source"
    - "network information flow with correlated sources"
    - "rate region of the quadratic gaussian two encoder source coding problem"

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)