human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "approximate feedback capacity of the gaussian multicast channel"):
  Abstract: We characterize the capacity region to within log{2(M-1)} bits/s/Hz for the M-transmitter K-receiver Gaussian multicast channel with feedback where each receiver wishes to decode every message from the M transmitters. Extending Cover-Leung's achievable scheme intended for (M,K)=(2,1), we show that this generalized scheme achieves the cutset-based outer bound within log{2(M-1)} bits per transmitter for all channel parameters. In contrast to the capacity in the non-feedback case, the feedback capacity improves upon the naive intersection of the feedback capacities of K individual multiple access channels. We find that feedback provides unbounded multiplicative gain at high signal-to-noise ratios as was shown in the Gaussian interference channel. To complement the results, we establish the exact feedback capacity of the Avestimehr-Diggavi-Tse (ADT) deterministic model, from which we make the observation that feedback can also be beneficial for function computation.

Includes members:
  Member "two way interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "two way function computation")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "lqg control approach to gaussian broadcast channels with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "youla coding and computation of gaussian feedback capacity")
  Member "interference channels with rate limited feedback":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity results for intermittent x channels with delayed channel state feedback")
  Member "feedback capacity of the gaussian interference channel to within 2 bits":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "capacity limits of full duplex cellular network")
  Member "feedback can double the prelog of some memoryless gaussian networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "insufficiency of linear feedback schemes in gaussian broadcast channels with common message")
  Member "noisy network coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an information theoretic analysis of the gaussian multicast channel with interactive user cooperation")
  Member "compound multiple access channels with partial cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "duality of a source coding problem and the semi deterministic broadcast channel with rate limited cooperation")

Question: Please tell me which class the source paper 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)