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: "an achievable region for a general multi terminal network and its chain graph representation"
  Abstract: Random coding, along with various standard techniques such as coded time-sharing, rate-splitting, superposition coding, and binning, are traditionally used in obtaining achievable rate regions for multi-terminal networks. The error analysis of such an achievable scheme relies heavily on the properties of strongly joint typical sequences and on bounds of the cardinality of typical sets. In this work, we obtain an achievable rate region for a general (i.e. an arbitrary set of messages shared amongst encoding nodes, which transmit to arbitrary decoding nodes) memoryless, single-hop, multi-terminal network without feedback or cooperation by introducing a general framework and notation, and carefully generalizing the derivation of the error analysis. We show that this general inner bound may be obtained from a graph representation that captures the statistical relationship among codewords and allows one to readily obtain the rate bounds that define the achievable rate region. The proposed graph representation naturally leads to the derivation of all the achievable schemes that can be generated by combining classic random coding techniques for any memoryless network used without feedback or cooperation.

Connected through hyperedge HE-1 (induced by source paper "primary rate splitting achieves capacity for the gaussian cognitive interference channel"):
  with members:
    - "the capacity of the semi deterministic cognitive interference channel and its application to constant gap results for the gaussian channel"
    - "new results on the capacity of the gaussian cognitive interference channel"
    - "state of the cognitive interference channel a new unified inner bound"

Connected through hyperedge HE-2 (induced by source paper "on the capacity of the interference channel with a cognitive relay"):
  with members:
    - "the dof of the k user interference channel with a cognitive relay"
    - "inner and outer bounds for the gaussian cognitive interference channel and new capacity results"
    - "a new capacity result for the z gaussian cognitive interference channel"
    - "the capacity of the semi deterministic cognitive interference channel and its application to constant gap results for the gaussian channel"
    - "new results on the capacity of the gaussian cognitive interference channel"
    - "symmetric capacity of the gaussian interference channel with an out of band relay to within 1 15 bits"
    - "outer bounds for the interference channel with a cognitive relay"
    - "new inner and outer bounds for the discrete memoryless cognitive interference channel and some capacity results"

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)