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 "exact channel synthesis"):
  Abstract: We consider the exact channel synthesis problem, which is the problem of determining how much information is required to create exact correlation remotely when there is a certain amount of randomness shared by two terminals. This problem generalizes an existing approximate version, in which the generated joint distribution is restricted to be close to a target distribution under the total variation (TV) distance measure, instead being exactly equal to the target distribution. We study the admissible region of the shared randomness rate and the communication rate for the exact channel synthesis problem by providing single-letter inner and outer bounds on it. The inner bound implies that a linear number of bits (or a finite rate) of shared randomness suffices to realize exact channel synthesis, even when communication rates are restricted to approach to the optimal communication rate $I(X;Y)$ asymptotically. This disproves a conjecture posed by Bennett-Devetak-Harrow-Shor-Winter (2014), where they conjectured that under this scenario, an exponential number of bits of shared randomness is necessary to realize exact channel synthesis. Furthermore, our bounds coincide for doubly symmetric binary sources (or binary symmetric channels), which implies that for such sources, the admissible rate region is completely characterized. We observe that for such sources, the admissible rate region for exact channel synthesis is strictly larger than that for TV-approximate version. We also extend these results to other sources, including Gaussian sources.

Includes members:
  Member "on exact and infty r enyi common informations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication for generating correlation a survey")
  Member "strong functional representation lemma and applications to coding theorems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication for generating correlation a unifying survey")
  Member "distributed simulation of continuous random variables":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "constrained functional value under general convexity conditions with applications to distributed simulation")
  Member "generalized common information common information extraction and private sources synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on exact and infty r enyi common informations")
  Member "exact common information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "communication for generating correlation a unifying survey")
  Member "wyner s common information generalizations and a new lossy source coding interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on exact and infty r enyi common informations")
  Member "simulation of a channel with another channel":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "communication for generating correlation a unifying survey")
  Member "distributed channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gaussian approximation of quantization error for estimation from compressed data")

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)