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: "posterior matching scheme for gaussian multiple access channel with feedback"
  Abstract: Posterior matching is a method proposed by Ofer Shayevitz and Meir Feder to design capacity achieving coding schemes for general point-to-point memoryless channels with feedback. In this paper, we present a way to extend posterior matching based encoding and variable rate decoding ideas for the Gaussian MAC with feedback, referred to as time-varying posterior matching scheme, analyze the achievable rate region and error probabilities of the extended encoding-decoding scheme. The time-varying posterior matching scheme is a generalization of the Shayevitz and Feder's posterior matching scheme when the posterior distributions of the input messages given output are not fixed over transmission time slots. It turns out that the well-known Ozarow's encoding scheme, which obtains the capacity of two-user Gaussian channel, is a special case of our extended posterior matching framework as the Schalkwijk-Kailath's scheme is a special case of the point-to-point posterior matching mentioned above. Furthermore, our designed posterior matching also obtains the linear-feedback sum-capacity for the symmetric multiuser Gaussian MAC. Besides, the encoding scheme in this paper is designed for the real Gaussian MAC to obtain that performance, which is different from previous approaches where encoding schemes are designed for the complex Gaussian MAC. More importantly, this paper shows potential of posterior matching in designing optimal coding schemes for multiuser channels with feedback.

Connected through hyperedge HE-1 (induced by source paper "sum rate capacity for symmetric gaussian multiple access channels with feedback"):
  with members:
    - "strengthening the entropy power inequality"
    - "dependence balance based outer bounds for gaussian networks with cooperation and feedback"
    - "variations on a theme by schalkwijk and kailath"
    - "outer bounds for multiple access channels with feedback using dependence balance"
    - "optimal feedback communication via posterior matching"
    - "on the gaussian mac with imperfect feedback"

Connected through hyperedge HE-2 (induced by source paper "on the capacity of symmetric gaussian interference channels with feedback"):
  with members:
    - "a novel time varying coding scheme for the gaussian broadcast channel with feedback"
    - "feedback capacity of the gaussian interference channel to within 2 bits"
    - "optimal feedback communication via posterior matching"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-3 (induced by source paper "posterior matching for gaussian broadcast channels with feedback"):
  with members:
    - "on the capacity of symmetric gaussian interference channels with feedback"
    - "mimo mac bc duality with linear feedback coding schemes"
    - "lqg control approach to gaussian broadcast channels with feedback"
    - "optimal feedback communication via posterior matching"
    - "the pre log of gaussian broadcast with feedback can be two"

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)