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 "an achievable region for a general multi terminal network and the corresponding 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 chain graph representation of the encoding operations. This graph representation 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. We also re-derive a few achievable regions for classic multi-terminal networks, such as the multi-access channel, the broadcast channel, and the interference channel, to show how this new representation allows one to quickly consider the possible choices of encoding/decoding strategies for any given network and the distribution of messages among the encoders and decoders.

Includes members:
  Member "interference networks with general message sets a random coding scheme":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity bounds for wireless ergodic fading broadcast channels with partial csit")
  Member "the capacity of the semi deterministic cognitive interference channel and its application to constant gap results for the gaussian channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multiuser cognitive radio networks an information theoretic perspective")
  Member "latent capacity region a case study on symmetric broadcast with common messages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an achievable rate region for two groupcast messages over the k user broadcast channel and capacity results for the combination network")
  Member "on the capacity of the interference channel with a cognitive relay":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi user cognitive interference channels a survey and new capacity results")
  Member "lecture notes on network information theory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the required number of antennas in a point to point large but finite mimo system outage limited scenario")
  Member "compute and forward harnessing interference through structured codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "private information retrieval over gaussian mac")
  Member "fundamental constraints on multicast capacity regions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an achievable rate region for two groupcast messages over the k user broadcast channel and capacity results for the combination network")
  Member "rate regions for relay broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sharp bounds for mutual covering")

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)