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: "fundamental limits of communications in interference networks part iv networks with a sequence of less noisy receivers"
  Abstract: In this fourth part of our multi-part papers, classes of interference networks with a sequence of less-noisy receivers are identified for which a successive decoding scheme achieve the sum-rate capacity. First, the two-receiver networks are analyzed: it is demonstrated that the unified outer bounds derived in Part III of our multi-part papers are sum-rate optimal for network scenarios which satisfy certain less-noisy conditions. Then, the multi-receiver networks are considered. These networks are far less understood. One of the main difficulties in the analysis of such scenarios is how to establish useful capacity outer bounds. In this paper, a novel technique requiring a sequential application of the Csiszar-Korner identity is developed to establish powerful single-letter outer bounds on the sum-rate capacity of multi-receiver interference networks which satisfy certain less-noisy conditions. By using these outer bounds, a full characterization of the sum-rate capacity is derived for general interference networks of arbitrary large sizes with a sequence of less-noisy receivers. Some generalizations of these outer bounds are also presented each of which is efficient to obtain the exact sum-rate capacity for various scenarios.

Connected through hyperedge HE-1 (induced by source paper "the k user interference channel strong interference regime"):
  with members:
    - "fundamental limits of communications in interference networks part iii information flow in strong interference regime"
    - "how much rate splitting is required for a random coding scheme a new achievable rate region for the broadcast channel with cognitive relays"
    - "fundamental limits of communications in interference networks part i basic structures"
    - "fundamental limits of communications in interference networks part ii information flow in degraded networks"
    - "interference networks with general message sets a random coding scheme"
    - "lecture notes on network information theory"
    - "capacity of symmetric k user gaussian very strong interference channels"

Connected through hyperedge HE-2 (induced by source paper "how much rate splitting is required for a random coding scheme a new achievable rate region for the broadcast channel with cognitive relays"):
  with members:
    - "fundamental limits of communications in interference networks part iii information flow in strong interference regime"
    - "capacity theorems for the cognitive radio channel with confidential messages"
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "fundamental limits of communications in interference networks part i basic structures"
    - "fundamental limits of communications in interference networks part ii information flow in degraded networks"
    - "interference networks with general message sets a random coding scheme"
    - "capacity bounds and exact results for the cognitive z interference channel"
    - "on the capacity of a class of cognitive z interference channels"

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)