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: "insufficiency of linear feedback schemes in gaussian broadcast channels with common message"
  Abstract: We consider the K 2-user memoryless Gaussian broadcast channel (BC) with feedback and common message only. We show that linear-feedback schemes with a message point, in the spirit of Schalkwijk&Kailath’s scheme for point-to-point channels or Ozarow&Leung’s scheme for BCs with private messages, are strictly suboptimal for this setup. Even with perfect feedback, the largest rate achieved by these schemes is strictly smaller than capacity C (which is the same with and without feedback). In the extreme case where the number of receivers K ! 1, the largest rate achieved by linear-feedback schemes with a message point tends to 0. To contrast this negative result, we describe a scheme for rate-limited feedback that uses the feedback in an intermittent way, i.e., the receivers send feedback signals only in few channel uses. This scheme achieves all rates R up to capacity C with an L-th order exponential decay of the probability of error if the feedback rate Rfb is at least (L 1)R for some positive integer L.

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"
    - "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"
    - "sending a bivariate gaussian source over a gaussian mac with feedback"

Connected through hyperedge HE-2 (induced by source paper "on the ozarow leung scheme for the gaussian broadcast channel with feedback"):
  with members:
    - "lqg control approach to gaussian broadcast channels with feedback"

Connected through hyperedge HE-3 (induced by source paper "coding schemes with rate limited feedback that improve over the nofeedback capacity for a large class of broadcast channels"):
  with members:
    - "the awgn bc with mac feedback a reduction to noiseless feedback via interaction"
    - "on the noisy feedback capacity of gaussian broadcast channels"
    - "feedback and partial message side information on the semideterministic broadcast channel"
    - "an achievable rate region for the broadcast channel with feedback"
    - "short message noisy network coding with a decode forward option"
    - "degrees of freedom of time correlated miso broadcast channel with delayed csit"
    - "optimal use of current and outdated channel state information degrees of freedom of the miso bc with mixed csit"
    - "lqg control approach to gaussian broadcast channels with feedback"

Connected through hyperedge HE-4 (induced by source paper "mimo mac bc duality with linear feedback coding schemes"):
  with members:
    - "the awgn bc with mac feedback a reduction to noiseless feedback via interaction"
    - "on the noisy feedback capacity of gaussian broadcast channels"
    - "on the ozarow leung scheme for the gaussian broadcast channel with feedback"
    - "an achievable rate region for the broadcast channel with feedback"
    - "any positive feedback rate increases the capacity of strictly less noisy broadcast channels"
    - "lqg control approach to gaussian broadcast channels with feedback"
    - "on the capacity of the discrete memoryless broadcast channel with feedback"

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)